Automatic camera angle switching in response to low noise audio to create combined audiovisual file

Information

  • Patent Grant
  • 11863858
  • Patent Number
    11,863,858
  • Date Filed
    Friday, September 23, 2022
    2 years ago
  • Date Issued
    Tuesday, January 2, 2024
    a year ago
Abstract
A system and method are provided for automatically concatenating two or more audiovisual clips containing video input from multiple cameras, and producing a combined audiovisual file containing video that switches between the two video inputs. In some examples, two video inputs and an audio input are recorded synchronously and are synchronized. The audio input can be sampled to locate low-noise audio events. The audiovisual file contains video that switches between two or more camera angles at the low-noise audio events. In one aspect, pauses are automatically removed from the audiovisual files. In another aspect, the system detects switch-initiating events, and switches between camera angles in response to detecting a switch-initiating event.
Description
BACKGROUND

Video interviews can be taped and used by recruiters to assist in representing candidates to potential employers. These videos can sometimes be one-dimensional and uninteresting.


Videos that cut between multiple views of the candidate can be more visually interesting, but editing and producing high-quality video is tedious and time-consuming.


SUMMARY

A system and method for automatically producing audiovisual files containing video from multiple cameras is provided. In some examples, a system is provided having a first video input and a second video input; an audio input; a time counter providing a timeline associated with the first video input, the second video input, and the audio input, the timeline enables a time synchronization of the first video input, the second video input, and the audio input; a non-transitory computer memory and a computer processor; and computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify a low noise audio segment in which the decibel level is below a threshold level for a predetermined period of time; and automatically assembling a combined audiovisual file by performing the steps of: retaining a first audiovisual clip can include a portion of the audio input and first video input occurring before the low noise audio segment, retaining a second audiovisual clip can include a portion of the audio input and second video input occurring after the low noise audio segment, and concatenating the first audiovisual clip and the second audiovisual clip to create a combined audiovisual file. In some examples, the first video input, the second video input, and the audio input are recorded synchronously, and the combined audiovisual file is a video interview of a job candidate.


In some examples, the first audiovisual clip ends at the low noise audio segment and the second audiovisual clip begins at the low noise audio segment. In some examples, the first audiovisual clip is earlier in the timeline than the second audiovisual clip, and the first audiovisual clip corresponds to a time immediately preceding the second audiovisual clip. In some examples, the predetermined period of time is at least two seconds. Some examples can further include computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify a beginning of the low noise audio segment and an end of the low noise audio segment; removing portions of the audio input, the first video input, and the second video input that fall between the beginning and end of the low noise audio segment; and concatenating the first audiovisual clip and the second audiovisual clip to create a combined audiovisual file that does not contain the low noise audio segment; the first audiovisual clip includes a portion of the audio input and first video input occurring before the beginning of the low noise audio segment, and the second audiovisual clip includes a portion of the audio input and the second video input occurring after the end of the low noise audio segment.


In some examples, the low noise audio segment is at least four seconds long. Some examples further include computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify multiple low noise audio segments in which the decibel level is below the threshold level for a predetermined period of time; and automatically concatenating alternating audiovisual clips that switch between the first video input and second video input after each low noise audio segment. Some examples further include computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify multiple low noise audio segments in which the decibel level is below the threshold level for at least the predetermined period of time; extracting content data from the first video input, the second video input, or the audio input to identify one or more switch-initiating events; automatically assembling a combined audiovisual file that switches between the first video input and the second video input following a switch-initiating event. In some examples, the switch-initiating events include one or more of: a gesture recognition event; a facial recognition event; a length of time of at least 30 seconds since a most recent camera angle switch; or a keyword extracted from the audio input via speech-to-text.


In some examples, a computer-implemented method includes receiving first video input of an individual from a first camera, receiving second video input of the individual from a second camera, receiving audio input of the individual from a microphone, the first video input, the second video input, and the audio input are recorded synchronously; sampling the audio input, the first video input, or the second video input to identify an event; automatically assembling a combined audiovisual file by performing the steps of: retaining a first audiovisual clip can include a portion of the first video input occurring before the event; retaining a second audiovisual clip can include a portion of the second video input occurring after the event; and concatenating the first audiovisual clip and the second audiovisual clip to create a combined audiovisual file containing video of the individual from two camera angles.


In some examples, the combined audiovisual file is a video interview of a job candidate. In some examples, the event is a low noise audio segment. Some examples further include the steps of: sampling the audio input to identify a plurality of low noise audio segments; retaining video clips that alternately switch between the first video input and the second video input following the low noise audio segments; and concatenating the alternating video clips to create a combined audiovisual file containing video that alternates between two camera angles. Some examples further include the step of extracting content data from the first video input, the second video input, or the audio input to identify one or more switch-initiating events, switching between the first video input and the second video input is only performed for low noise audio segments that follow switch-initiating events.


In some examples, the content data is at least one of: facial recognition; gesture recognition; posture recognition; or keywords extracted using speech-to-text. Some examples further include the steps of: sampling the audio input to identify multiple extended low noise audio segments that are at least four seconds long; removing the portions of the audio input, the first video input, and the second video input that fall between the beginning and end of the extended low noise audio segments; concatenating video clips containing alternating portions of the first video input and portions of the second video input to create a combined audiovisual file that does not contain audio or video occurring between the beginning and end of extended low noise audio segments.


In some examples, a system is included having a first video input and a second video input; an audio input; a time counter providing a timeline associated with the first video input, the second video input, and the audio input, the timeline enables a time synchronization of the first video input, the second video input, and the audio input; a non-transitory computer memory and a computer processor; and computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify a low noise audio segment in which the decibel level is below a threshold level for a predetermined period of time; and automatically assembling a combined audiovisual file by performing the steps of: retaining a first audiovisual clip can include a portion of the first video input and synchronized audio input occurring before the low noise audio segment; retaining a second audiovisual clip can include a portion of the second video input and synchronized audio input occurring after the low noise audio segment; and concatenating the first audiovisual clip and the second audiovisual clip to create a combined audiovisual file.


In some examples, the first video input, the second video input, and the audio input are recorded synchronously, and the combined audiovisual file is a video interview of a job candidate. Some examples further include computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify a plurality of low noise audio segments in which the decibel level is below the threshold level for the predetermined period of time; and concatenating a plurality of audiovisual clips that switch between the first video input and the second video input after each low noise audio segment to create a combined audiovisual file containing video that alternates between two camera angles.


This summary is an overview of some of the teachings of the present application and is not intended to be an exclusive or exhaustive treatment of the present subject matter. Further details are found in the detailed description and appended claims. Other aspects will be apparent to persons skilled in the art upon reading and understanding the following detailed description and viewing the drawings that form a part thereof, each of which is not to be taken in a limiting sense.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 is a perspective view of a multi-camera kiosk according to some examples.



FIG. 2 is a schematic view of a kiosk system according to some examples.



FIG. 3 illustrates an example of multiple video inputs.



FIG. 4 is a graph of decibel level versus time for an audio input according to some examples.



FIG. 5 visually illustrates a method of automatically concatenating audiovisual clips into an audiovisual file according to some examples.



FIG. 6 visually illustrates a method of removing pauses from audio and video inputs and automatically concatenating audiovisual clips into an audiovisual file according to some examples.



FIG. 7 visually illustrates a method of automatically concatenating audiovisual clips into an audiovisual file in response to an event according to some examples.





DETAILED DESCRIPTION

The present disclosure relates to a system and method for producing audiovisual files containing video that automatically cuts between video footage from multiple cameras. The multiple cameras can be arranged during recording such that they each focus on a subject from a different camera angle, providing multiple viewpoints of the subject. The system can be used for recording a person who is speaking, such as in a video interview. Although the system will be described in the context of a video interview, other uses are contemplated and are within the scope of the technology. For example, the system could be used to record educational videos, entertaining or informative speaking, or other situations in which an individual is being recorded with video and audio.


Some implementations of the technology provide a kiosk or booth that houses multiple cameras and a microphone. The cameras each produce a video input to the system, and the microphone produces an audio input. A time counter provides a timeline associated with the multiple video inputs and the audio input. The timeline enables video input from each camera to be time-synchronized with the audio input from the microphone.


Multiple audiovisual clips are created by combining video inputs with a corresponding synchronized audio input. The system detects events in the audio input, video inputs, or both the audio and video inputs, such as a pause in speaking corresponding to low-audio input. The events correspond to a particular time in the synchronization timeline. To automatically assemble audiovisual files, the system concatenates a first audiovisual clip and a second audiovisual clip. The first audiovisual clip contains video input before the event, and the second audiovisual clip contains video input after the event. The system can further create audiovisual files that concatenate three or more audiovisual clips that switch between particular video inputs after predetermined events.


One example of an event that can be used as a marker for deciding when to cut between different video clips is a drop in the audio volume detected by the microphone. During recording, the speaker may stop speaking briefly, such as when switching between topics, or when pausing to collect their thoughts. These pauses can correspond to a significant drop in audio volume. In some examples, the system looks for these low-noise events in the audio track. Then, when assembling an audiovisual file of the video interview, the system can change between different cameras at the pauses. This allows the system to automatically produce high quality, entertaining, and visually interesting videos with no need for a human editor to edit the video interview. Because the quality of the viewing experience is improved, the viewer is likely to have a better impression of a candidate or other speaker in the video. A higher quality video better showcases the strengths of the speaker, providing benefits to the speaker as well as the viewer.


In another aspect, the system can remove unwanted portions of the video automatically based on the contents of the audio or video inputs, or both. For example, the system may discard portions of the video interview in which the individual is not speaking for an extended period of time. One way this can be done is by keeping track of the length of time that the audio volume is below a certain volume. If the audio volume is low for an extended period of time, such as a predetermined number of seconds, the system can note the time that the low noise segment begins and ends. A first audiovisual clip that ends at the beginning of the low noise segment can be concatenated with a second audiovisual clip that begins at the end of the low noise segment. The audio input and video inputs that occur between the beginning and end of the low noise segment can be discarded. In some examples, the system can cut multiple pauses from the video interview, and switch between camera angles multiple times. This eliminates dead air and improves the quality of the video interview for a viewer.


In another aspect, the system can choose which video input to use in the combined audiovisual file based on the content of the video input. For example, the video inputs from the multiple cameras can be analyzed to look for content data to determine whether a particular event of interest takes place. As just one example, the system can use facial recognition to determine which camera the individual is facing at a particular time. The system then can selectively prefer the video input from the camera that the individual is facing at that time in the video. As another example, the system can use gesture recognition to determine that the individual is using their hands when talking. The system can selectively prefer the video input that best captures the hand gestures. For example, if the candidate consistently pivots to the left while gesturing, a right camera profile shot might be subjectively better than minimizing the candidate's energy using the left camera feed. Content data such as facial recognition and gesture recognition can also be used to find events that the system can use to decide when to switch between different camera angles.


In another aspect, the system can choose which video input to use based on a change between segments of the interview, such as between different interview questions.


Turning now to the figures, an example implementation of the disclosed technology will be described in relation to a kiosk for recording video interviews. However, it should be understood that this implementation is only one possible example, and other set ups could be used to implement the disclosed technology.


Video Interview Kiosk (FIG. 1)



FIG. 1 shows a kiosk 101 for recording a video interview of an individual 112. The kiosk 101 is generally shaped as an enclosed booth 105. The individual 112 can be positioned inside of the enclosed booth 105 while being recorded. Optionally, a seat 107 is provided for the individual 112. The kiosk 101 houses multiple cameras, including a first camera 122, a second camera 124, and a third camera 126. Each of the cameras is capable of recording video of the individual 112 from different angles. In the example of FIG. 1, the first camera 122 records the individual 112 from the left side, the second camera 124 records the individual 112 from the center, and the third camera 126 records the individual 112 from the right side. In some examples, the camera 124 can be integrated into a user interface 133 on a tablet computer 131. The user interface 133 can prompt the individual to answer interview questions. A microphone 142 is provided for recording audio.


The first, second, and third cameras 122, 124, 126 can be digital video cameras that record video in the visible spectrum using, for example, a CCD or CMOS image sensor. Optionally, the cameras can be provided with infrared sensors or other sensors to detect depth, movement, etc.


In some examples, the various pieces of hardware can be mounted to the walls of the enclosed booth 105 on a vertical support 151 and a horizontal support 152. The vertical support 151 can be used to adjust the vertical height of the cameras and user interface, and the horizontal support 152 can be used to adjust the angle of the cameras 122, 124, 126.


Schematic of Kiosk and Edge Server (FIG. 2)



FIG. 2 shows a schematic diagram of one example of the system. The kiosk 101 includes an edge server 201 that has a computer processor 203, a system bus 207, a system clock 209, and a non-transitory computer memory 205. The edge server 201 is configured to receive input from the video and audio devices of the kiosk and process the received inputs.


The kiosk 101 can further include the candidate user interface 133 in data communication with the edge server 201. An additional user interface 233 can be provided for a kiosk attendant. The attendant user interface 233 can be used, for example, to check in users, or to enter data about the users. The candidate user interface 133 and the attendant user interface 233 can be provided with a user interface application program interface (API) 235 stored in the memory 205 and executed by the processor 203. The user interface API 235 can access particular data stored in the memory 205, such as interview questions 237 that can be displayed to the individual 112 on in the user interface 133. The user interface API 235 can receive input from the individual 112 to prompt a display of a next question once the individual has finished answering a current question.


The system includes multiple types of data inputs. In one example, the camera 122 produces a video input 222, the camera 124 produces a video input 224, and the camera 126 produces a video input 226. The microphone 142 produces an audio input 242. The system also receives behavioral data input 228. The behavioral data input 228 can be from a variety of different sources. In some examples, the behavioral data input 228 is a portion of data received from one or more of the cameras 122, 124, 126. In other words, the system receives video data and uses it as the behavioral data input 228. In some examples, the behavioral data input 228 is a portion of data received from the microphone 142. In some examples, the behavioral data input 228 is sensor data from one or more infrared sensors provided on the cameras 122, 124, 126. The system can also receive text data input 221 that can include text related to the individual 112, and candidate materials 223 that can include materials related to the individual's job candidacy, such as a resume.


In some examples, the video inputs 222, 224, 226 are stored in the memory 205 of the edge server 201 as video files 261. In alternative examples, the video inputs 222, 224, 226 are processed by the processor 203, but are not stored separately. In some examples, the audio input 242 is stored as audio files 262. In alternative examples, the audio input 242 is not stored separately. The candidate materials input 223, text data input 221, and behavioral data input 228 can also be optionally stored or not stored as desired.


In some examples, the edge server 201 further includes a network communication device 271 that enables the edge server 201 to communicate with a remote network 281. This enables data that is received and/or processed at the edge server 201 to be transferred over the network 281 to a candidate database server 291.


The edge server 201 includes computer instructions stored on the memory 205 to perform particular methods. The computer instructions can be stored as software modules. As will be described below, the system can include an audiovisual file processing module 263 for processing received audio and video inputs and assembling the inputs into audiovisual files and storing the assembled audiovisual files 264. The system can include a data extraction module 266 that can receive one or more of the data inputs (video inputs, audio input, behavioral input, etc.) and extract behavior data 267 from the inputs and store the extracted behavior data 267 in the memory 205.


Automatically Creating Audiovisual Files from Two or More Video Inputs (FIGS. 3-7) The disclosed system and method provide a way to take video inputs from multiple cameras and arrange them automatically into a single audiovisual file that cuts between different camera angles to create a visually interesting product.



FIG. 3 illustrates video frames of video inputs received from different cameras. In this example, video frame 324 is part of the video input 224 that is received from the second camera 124, which focuses on the individual 112 from a front and center angle. This video input is designated as “Video 1” or simply “Vid1.” The video frame 322 is part of the video input 222 from the first camera 122, which focuses on the individual 112 from the individual 112's left side. This video input is designated as “Video 2” or simply “Vid2.” The video frame 326 is part of the video input 226 from the third camera 126, which focuses on the individual 112 from the individual 112's right side. This video input is designated as “Video 3” or simply “Vid3.” These video inputs can be provided using any of a number of different types of video coding formats. These include but are not limited to MPEG-2 Part 2, MPEG-4 Part 2, H.264 (MPEG-4 Part 10), HEVC, and AV1.


Audio inputs 242 can also be provided using any of a number of different types of audio compression formats. These can include but are not limited to MP1, MP2, MP3, AAC, ALAC, and Windows Media Audio.


The system takes audiovisual clips recorded during the video interview and concatenates the audiovisual clips to create a single combined audiovisual file containing video of an individual from multiple camera angles. In some implementations, a system clock 209 creates a timestamp associated with the video inputs 222, 224, 226 and the audio input 242 that allows the system to synchronize the audio and video based on the timestamp. A custom driver can be used to combine the audio input with the video input to create an audiovisual file.


As used herein, an “audiovisual file” is a computer-readable container file that includes both video and audio. An audiovisual file can be saved on a computer memory, transferred to a remote computer via a network, and played back at a later time. Some examples of video encoding formats for an audiovisual file compatible with this disclosure are MP4 (mp4, m4a, mov); 3GP (3gp, 3gp2, 3g2, 3gpp, 3gpp2); WMV (wmy, wma); AVI; and QuickTime.


As used herein, an “audiovisual clip” is a video input combined with an audio input that is synchronized with the video input. For example, the system can record an individual 112 speaking for a particular length of time, such as 30 seconds. In a system that has three cameras, three audiovisual clips could be created from that 30 second recording: a first audiovisual clip can contain the video input 224 from Vid1 synchronized with the audio input 242 from t=0 to t=30 seconds. A second audiovisual clip can contain the video input 222 from Vid2 synchronized with the audio input 242 from t=0 to t=30 seconds. A third audiovisual clip can contain the video input 226 from Vid3 synchronized with the audio input 242 from t=0 to t=30 seconds; Audiovisual clips can be created by processing a video input stream and an audio input stream which are then stored as an audiovisual file. An audiovisual clip as described herein can be, but is not necessarily stored in an intermediate state as a separate audiovisual file before being concatenated with other audiovisual clips. As will be described below, in some examples, the system will select one video input from a number of available video inputs, and use that video input to create an audiovisual clip that will later be saved in an audiovisual file. In some examples, the unused video inputs may be discarded.


Audiovisual clips can be concatenated. As used herein, “concatenated” means adding two audiovisual clips together sequentially in an audiovisual file. For example, two audiovisual clips that are each 30 seconds long can be combined to create a 60-second long audiovisual file. In this case, the audiovisual file would cut from the first audiovisual clip to the second audiovisual clip at the 30 second mark.


During use, each camera in the system records an unbroken sequence of video, and the microphone records an unbroken sequence of audio. An underlying time counter provides a timeline associated with the video and audio so that the video and audio can be synchronized.


In one example of the technology, the system samples the audio track to automatically find events that are used to triggered the system to cut between video inputs when producing an audiovisual file. In one example, the system looks for segments in the audio track in which the volume is below a threshold volume. These will be referred to as low noise audio segments.



FIG. 4 is a graph 411 representing the audio volume in an audio track over time. The graph conceptually shows the audio volume of the audio input in decibels (D) versus time in seconds (t). In some examples, the system uses a particular threshold volume as a trigger to determine when to cut between the video inputs. For example, in FIG. 4, the threshold level is 30 decibels. One method of finding low noise audio segments is to calculate an average decibel level over a particular range of time, such as 4 seconds. If the average decibel level during that period of time is below the threshold level, the system will mark this as a low noise audio segment.


Applying this method to FIG. 4, the system computes the average (mean) volume over each four-second interval for the entire length of the audio track, in this case, in the range between t=0 and t=35. Consider an average decibel level over a four second interval between t=5 and t=9. In this case, although the volume falls below 30 decibels for a short period of time, the average volume over that four second period is greater than 30 decibels, and therefore this would not be considered a low noise audio segment. Over the four second interval from t=11 to t=15 seconds, the average volume is less than 30 decibels, and therefore this would be considered a low noise audio segment. In some examples, as soon the system detects an event corresponding to a low noise audio segment, the system marks that time as being a trigger to switch between video inputs.


In some examples, the system marks the beginning and end of the low noise audio segments to find low noise audio segments of a particular length. In this example, the system computes the average (mean) volume over each four second interval, and as soon the average volume is below the threshold volume (in this case 30 decibels), the system marks that interval as corresponding to the beginning of the low noise audio segment. The system continues to sample the audio volume until the average audio volume is above the threshold volume. The system then marks that interval as corresponding to the end of the low noise audio segment.


The system uses the low noise audio segments to determine when to switch between camera angles. After finding and interval corresponding to the beginning or end of the low noise audio segments, the system determines precisely at which time to switch. This can be done in a number of ways, depending upon the desired result.


In the example of FIG. 4, the system could determine that the average volume of the four second interval between =10 and t=12 drops below the threshold volume. The system could use the end of that interval (t=12) to be the time to switch. Alternatively, the system could determine that the average volume of the four-second interval between t=18 and t=22 increases above the threshold volume, and determine that the beginning of that interval (t=18) as the time to switch. The system could also use the midpoint of the beginning and end of the intervals to switch (i.e., midway between t=12 and t=18). Other methods of determining precisely when in the timeline to make the switch are possible, and are within the scope of the technology.


In some examples, the system is configured to discard portions of the video and audio inputs that correspond to a portion of the low noise audio segments. This eliminates dead air and makes the audiovisual file more interesting for the viewer. In some examples, the system only discards audio segments that our at least a predetermined length of time, such as at least 2 seconds, at least 4 seconds, at least 6 seconds, at least 8 seconds, or at least 10 seconds. This implementation will be discussed further in relation to FIG. 6.


Automatically Concatenating Audiovisual Clips (FIG. 5)



FIG. 5 illustrates a system and method for automatically creating a combined audiovisual file containing video images from two or more video inputs. For the sake of simplicity, only two video inputs are illustrated in FIG. 5. It should be understood, however, that the method and system could be adapted to any number of video inputs.


The system includes two video inputs: Video 1 and Video 2. The system also includes an Audio input. In the example of FIG. 5, the video inputs and the audio input are recorded simultaneously. The two video inputs and the audio input are each recorded as an unbroken sequence. A time counter, such as the system clock 209, provides a timeline 501 that enables a time synchronization of the two video inputs and the audio input. The recording begins at time t0 and ends at time tn.


In the example of FIG. 5, the system samples the audio track to determine low noise audio segments. For example, the system can use the method as described in relation to FIG. 4; however, other methods of determining low noise audio segments are contemplated, and are within the scope of the disclosed technology.


Sampling the audio track, the system determines that at time t1, a low noise audio event occurred. The time segment between t=t0 and t=t1 is denoted as Seg1. To assemble a combined audiovisual file 540, the system selects an audiovisual clip 541 combining one video input from Seg1 synchronized with the audio from Seg1, and saves this audiovisual clip 541 as a first segment of the audiovisual file 540—in this case, Vid1.Seg1 (Video 1 Segment 1) and Aud.Seg1 (audio Segment 1). In some examples, the system can use a default video input as the initial input, such as using the front-facing camera as the first video input for the first audiovisual clip. In alternative examples, the system may sample content received while the video and audio are being recorded to prefer one video input over another input. For example, the system may use facial or gesture recognition to determine that one camera angle is preferable over another camera angle for that time segment. Various alternatives for choosing which video input to use first are possible, and are within the scope of the technology.


The system continues sampling the audio track, and determines that at time t2, a second low noise audio event occurred. The time segment between t=t1 and t=t2 is denoted as Seg2. For this second time segment, the system automatically switches to the video input from Video 2, and saves a second audiovisual clip 542 containing Vid2.Seg2 and Aud.Seg2. The system concatenates the second audiovisual clip 542 and the first audiovisual clip 541 in the audiovisual file 540.


The system continues sampling the audio track, and determines that at time t3, a third low noise audio event occurred. The time segment between t=t2 and t=t3 is denoted as Seg3. For this third time segment, the system automatically cuts back to the video input from Video 1, and saves a third audiovisual clip 543 containing Vid1.Seg3 and Aud.Seg3. The system concatenates the second audiovisual clip 542 and the third audiovisual clip 543 in the audiovisual file 540.


The system continues sampling the audio track, and determines that at time t4, a fourth low noise audio event occurred. The time segment between t=t3 and t=t4 is denoted as Seg4. For this fourth time segment, the system automatically cuts back to the video input from Video 2, and saves a fourth audiovisual clip 544 containing Vid2.Seg4 and Aud.Seg4. The system concatenates the third audiovisual clip 543 and the fourth audiovisual clip 544 in the audiovisual file 540.


The system continues sampling the audio track, and determines that no additional low noise audio events occur, and the video input and audio input stop recording at time t1. The time segment between t=t4 and t=tn is denoted as Seg5. For this fifth time segment, the system automatically cuts back to the video input from Video 1, and saves a fifth audiovisual clip 545 containing Vid1.Seg5 and Aud.Seg5. The system concatenates the fourth audiovisual clip 544 and the fifth audiovisual clip 545 in the audiovisual file 540.


In some examples, audio sampling and assembling of the combined audiovisual file is performed in real-time as the video interview is being recorded. In alternative examples, the video input and audio input can be recorded, stored in a memory, and processed later to create a combined audiovisual file. In some examples, after the audiovisual file is created, the raw data from the video inputs and audio input is discarded.


Automatically Removing Pauses and Concatenating Audiovisual Clips (FIG. 6)


In another aspect of the technology, the system can be configured to create combined audiovisual files that remove portions of the interview in which the subject is not speaking. FIG. 6 illustrates a system and method for automatically creating a combined audiovisual file containing video images from two or more video input, where a portion of the video input and audio input corresponding to low noise audio segments are not included in the combined audiovisual file. For the sake of simplicity, only two video inputs are illustrated in FIG. 6. It should be understood, however, that the method and system could be adapted to any number of video inputs.


In the example of FIG. 6, the system includes a video input Video 1 and Video number two. The system also includes an Audio input. The video inputs and the audio input are recorded simultaneously in an unbroken sequence. A time counter, such as the system clock 209, provides a timeline 601 that enables a time synchronization of the two video inputs and the audio input. The recording begins at time to and ends at time tn.


As in the example of FIG. 5, the system samples the audio track to determine low noise audio segments. In FIG. 6, the system looks for the beginning and end of low noise audio segments, as described above with relation to FIG. 4. Sampling the audio track, the system determines that at time t1, a low noise audio segment begins, and at time t2, the low noise audio segment ends. The time segment between t=t0 and t=t1 is denoted as Seg1. To assemble a combined audiovisual file 640, the system selects an audiovisual clip 641 combining one video input from Seg1 synchronized with the audio from Seg1, and saves this audiovisual clip 641 as a first segment of the audiovisual file 640 in this case, Vid1.Seg1 (Video 1 Segment 1) and Aud.Seg1 (audio Segment 1). The system then disregards the audio inputs and video inputs that occur during Seg2, the time segment between t=t1 and t=t2.


The system continues sampling the audio track, and determines that at time t3, a second low noise audio segment begins, and at time t4, the second low noise audio segment ends. The time segment between t=t2 and t=t3 is denoted as Seg3. For this time segment, the system automatically switches to the video input from Video 2, and saves a second audiovisual clip 642 containing Vid2.Seg3 and Aud.Seg3. The system concatenates the second audiovisual clip 642 and the first audiovisual clip 641 in the audiovisual file 640.


The system continues sampling the audio input to determine the beginning and end of further low noise audio segments. In the example of FIG. 6, Seg6 is a low noise audio segment beginning at time t5 and ending at time t6. Seg 8 is a low noise audio segment beginning at time t7 and ending at time t8. The system removes the portions of the audio input and video inputs that fall between the beginning and end of the low noise audio segments. At the same time, the system automatically concatenates retained audiovisual clips, switching between the video inputs after the end of each low noise audio segment. The system concatenates the audiovisual clips 643, 644, and 645 to complete the audiovisual file 640. The resulting audiovisual file 640 contains audio from segments 1, 3, 5, 7, and 9. The audiovisual file 640 does not contain audio from segments 2, 4, 6, or 8. The audiovisual file 640 contains alternating video clips from Video 1 and Video 2 that switch between the first video input and the second video input after each low noise audio segment.


Automatically Concatenating Audiovisual Clips with Camera Switching in Response to Switch-Initiating Events (FIG. 7)


In another aspect of the technology, the system can be configured to switch between the different video inputs in response to events other than low noise audio segments. These events will be generally categorized as switch-initiating events. A switch-initiating event can be detected in the content of any of the data inputs that are associated with the timeline. “Content data” refers to any of the data collected during the video interview that can be correlated or associated with a specific time in the timeline. These events are triggers that the system uses to decide when to switch between the different video inputs. For example, behavioral data input, which can be received from an infrared sensor or present in the video or audio, can be associated with the timeline in a similar manner that the audio and video images are associated with the timeline. Facial recognition data, gesture recognition data, and posture recognition data can be monitored to look for switch-initiating events. For example, if the candidate turns away from one of the video cameras to face a different video camera, the system can detect that motion and note it as a switch-initiating event. Hand gestures or changes in posture can also be used to trigger the system to cut from one camera angle to a different camera angle.


As another example, the audio input can be analyzed using speech to text software, and the resulting text can be used to find keywords that trigger a switch. In this example, the words used by the candidate during the interview would be associated with a particular time in the timeline.


Another type of switch-initiating event can be the passage of a particular length of time. A timer can be set for a number of seconds that is the maximum desirable amount of time for a single segment of video. For example, an audiovisual file can feel stagnant and uninteresting if the same camera has been focusing on the subject for more than 90 seconds. The system clock can set a 90 second timer every time that a camera switch occurs. If it is been greater than 90 seconds since the most recent switch-initiating event, expiration of the 90 second timer can be used as the switch-initiating event. Other amounts of time could be used, such as 30 seconds, 45 seconds, 60 seconds, etc., depending on the desired results.


Conversely, the system clock can set a timer corresponding to a minimum number of seconds that must elapse before a switch between two video inputs. For example, the system could detect multiple switch-initiating events in rapid succession, and it may be undesirable to switch back-and-forth between two video inputs too quickly. To prevent this, the system clock could set a timer for 30 seconds, and only register switch-initiating events that occur after expiration of the 30 second timer. Though resulting combined audiovisual file would contain audiovisual clip segments of 30 seconds or longer.


Another type of switch-initiating event is a change between interview questions that the candidate is answering, or between other segments of a video recording session. In the context of an interview, the user interface API 235 (FIG. 2) can display interview questions so that the individual 112 can read each interview question and then respond to it verbally. The user interface API can receive input, such as on a touch screen or input button, to indicate that one question has been answered, and prompt the system to display the next question. The prompt to advance to the next question can be a switch-initiating event.


Turning to FIG. 7, the system includes two video inputs: Video 1 and Video 2. The system also includes an Audio input. In the example of FIG. 7, the video inputs and the audio input are recorded simultaneously. The two video inputs and the audio input are each recorded as an unbroken sequence. A time counter, such as the system clock 209, provides a timeline 701 that enables a time synchronization of the two video inputs and the audio input. The recording begins at time to and ends at time tn. In some examples, the system of FIG. 7 further includes behavioral data input associated with the timeline 701.


In the example of FIG. 7, the system automatically samples the audio input for low noise audio segments in addition to detecting switch-initiating events. The system can sample the audio input using the method as described in relation to FIG. 4; however, other methods of determining low noise audio segments are contemplated, and are within the scope of the disclosed technology.


In FIG. 7, the audio track is sampled in a manner similar to that of FIG. 5. The system determines that at time t1, a low noise audio event occurred. The time segment between t=t0 and t=t1 is denoted as Aud.Seg1. However, no switch-initiating event was detected during Aud.Seg1. Therefore, unlike the system of FIG. 5, the system does not switch video inputs.


At time t2, the system detects a switch-initiating event. However, the system does not switch between camera angles at time t2, because switch-initiating events can occur at any time, including during the middle of a sentence. Instead, the system in FIG. 7 continues sampling the audio input to find the next low noise audio event. This means that a switch between two camera angles is only performed after two conditions have been met: the system detects a switch-initiating event, and then, after the switch-initiating event, the system detects a low noise audio event.


In some examples, instead of continuously sampling the audio track for low noise audio events, the system could wait to detect a switch-initiating event, then begin sampling the audio input immediately after the switch-initiating event. The system would then cut from one video input to the other video input at the next low noise audio segment.


At time t3, the system determines that another low noise audio segment has occurred. Because this low noise audio segment occurred after a switch-initiating event, the system begins assembling a combined audiovisual file 740 by using an audiovisual clip 741 combining one video input (in this case, Video 1) with synchronized audio input for the time segment t=t0 through t=t3.


The system then waits to detect another switch-initiating event. In the example of FIG. 7, the system finds another low noise audio event at t4, but no switch-initiating event has yet occurred. Therefore, the system does not switch to the second video input. At time t5, the system detects a switch-initiating event. The system then looks for the next low noise audio event, which occurs at time t6. Because time t6 is a low noise audio event that follows a switch-initiating event, the system takes the audiovisual clip 742 combining video input from Video 2 and audio input from the time segment from t=t3 to t=t6. The audiovisual clip 741 is concatenated with the audiovisual clip 742 in the audiovisual file 740.


The system then continues to wait for a switch-initiating event. In this case, no switch-initiating event occurs before the end of the video interview at time tn. The audiovisual file 740 is completed by concatenating an alternating audiovisual clip 743 containing video input from Video 1 to the end of the audiovisual file 740.


The various methods described above can be combined in a number of different ways to create entertaining and visually interesting audiovisual interview files. Multiple video cameras can be used to capture a candidate from multiple camera angles. Camera switching between different camera angles can be performed automatically with or without removing audio and video corresponding to long pauses when the candidate is not speaking. Audio, video, and behavioral inputs can be analyzed to look for content data to use as switch-initiating events, and/or to decide which video input to use during a particular segment of the audiovisual file. Some element of biofeedback can be incorporated to favor one video camera input over the others.


As used in this specification and the appended claims, the singular forms include the plural unless the context clearly dictates otherwise. The term “or” is generally employed in the sense of “and/or” unless the content clearly dictates otherwise. The phrase “configured” describes a system, apparatus, or other structure that is constructed or configured to perform a particular task or adopt a particular configuration. The term “configured” can be used interchangeably with other similar terms such as arranged, constructed, manufactured, and the like.


All publications and patent applications referenced in this specification are herein incorporated by reference for all purposes.


While examples of the technology described herein are susceptible to various modifications and alternative forms, specifics thereof have been shown by way of example and drawings. It should be understood, however, that the scope herein is not limited to the particular examples described. On the contrary, the intention is to cover modifications, equivalents, and alternatives falling within the spirit and scope herein.

Claims
  • 1. A system comprising: a first video input from a first video camera and a second video input from a second video camera, wherein the first video camera and the second video camera are directed towards a common area, such that the video cameras are configured to obtain video data of a common subject in the common area from different angles, wherein the first video input and the second video input are recorded simultaneously and are synchronized;an audio input, wherein the audio input is recorded simultaneously and is synchronized with the first video input and the second video input;a non-transitory computer memory and a computer processor; and computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify a first low noise audio segment in which a decibel level is below a threshold level for a predetermined period of time and to identify a beginning of the first low noise audio segment;sampling the audio input to identify a second low noise audio segment in which a decibel level is below the threshold level for the predetermined period of time and to identify a beginning of the second low noise audio segment;determining an amount of time between the first low noise audio segment and a second low noise audio segment;producing a combined audiovisual production, wherein the combined audiovisual production comprises: a first audiovisual clip, the first audiovisual clip comprising: a portion of the audio input, anda portion of the first video input occurring before the first low noise audio segment, wherein the first audiovisual clip ends after the beginning of the first low noise audio segment and before an end of the first low noise audio segment,a second audiovisual clip, the second audio visual clip comprising: a portion of the audio input, anda portion of the second video input occurring immediately after an end of the portion of the first video input in the first audiovisual clip, the second audiovisual clip begins after the beginning of the first low noise audio segment and before the end of the first low noise audio segment, anda third audiovisual clip, the third audiovisual clip comprising: a portion of the audio input, and(1) if the amount of time between the first low noise audio segment and the second low noise audio segment is greater than a switch delay time period, a portion of the first video input occurring immediately after an end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second low noise audio segment and before the end of the second low noise audio segment, or(2) if the amount of time between the first low noise audio segment and the second low noise audio segment is not greater than the switch delay time period, a portion of the second video input occurring immediately after an end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second low noise audio segment and before the end of the second low noise audio segment.
  • 2. The system of claim 1, wherein the first video input, the second video input, and the audio input are recorded synchronously.
  • 3. The system of claim 1, wherein the combined audiovisual production is a video interview of a job candidate.
  • 4. The system of claim 1, further comprising computer instructions stored on the memory for instructing the processor to perform the steps of: sampling the audio input to identify multiple low noise audio segments in which the decibel level is below the threshold level for a predetermined period of time; andautomatically concatenating alternating audiovisual clips that switch between the first video input and second video input after each low noise audio segment.
  • 5. The system of claim 1, further comprising computer instructions stored on the memory for instructing the processor to perform the steps of: extracting content data from the first video input, the second video input, or the audio input to identify one or more switch-initiating events;automatically assembling a combined audiovisual production that switches between the first video input and the second video input following a switch-initiating event.
  • 6. The system of claim 5, wherein the switch-initiating event is a keyword extracted from the audio input via speech-to-text.
  • 7. The system of claim 1, wherein the combined audiovisual production has a length of time equivalent to a length of time of the first video input, the second video input and the audio input.
  • 8. The system of claim 1, wherein when the first audiovisual clip ends after the beginning of the first low noise audio segment and before the end of the first low noise audio segment and the second audiovisual clip begins after the beginning of the first low noise audio segment and before the end of the first low noise audio segment.
  • 9. A computer-implemented method comprising: receiving first video input from a first video camera;receiving second video input from a second video camera, wherein the first video camera and the second video camera are directed to a common area, such that the video cameras are configured to obtain video data of a common subject in the common area from different angles;receiving audio input from a microphone, wherein the first video input, the second video input and the audio input are recorded simultaneously and are synchronized;sampling the audio input to identify a first low noise audio segment, wherein the first low noise audio segment has a decibel level that is below a threshold level for a period of time, and to identify a second low noise audio segment, wherein the second low noise audio segment has a decibel level that is below the threshold level for the period of time;outputting an audiovisual production, wherein the audiovisual production comprises: a first audiovisual clip, the first audiovisual clip comprising: a portion of the audio input, anda portion of the first video input occurring before the first low noise audio segment, wherein the first audiovisual clip ends after the beginning of the first low noise audio segment and before an end of the first low noise audio segment,a second audiovisual clip, the second audio visual clip comprising: a portion of the audio input, anda portion of the second video input occurring immediately after an end of the portion of the first video input in the first audiovisual clip, the second audiovisual clip begins after the beginning of the first low noise audio segment and before the end of the first low noise audio segment, anda third audiovisual clip, the third audiovisual clip comprising: a portion of the audio input, and(1) if the amount of time between the first low noise audio segment and the second low noise audio segment is greater than a switch delay time period, a portion of the first video input occurring immediately after an end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second low noise audio segment and before the end of the second low noise audio segment, or(2) if the amount of time between the first low noise audio segment and the second low noise audio segment is not greater than the switch delay time period, a portion of the second video input occurring immediately after an end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second low noise audio segment and before the end of the second low noise audio segment.
  • 10. The method of claim 9, wherein the output audiovisual production is a video interview of a job candidate.
  • 11. The method of claim 9, wherein the first video input, the second video input, and the audio input are recorded synchronously.
  • 12. The method of claim 9, further comprising the steps of: retaining video clips that alternately switch between the first video input and the second video input following the low noise audio segments the occur at least more than the switch delay time period after the previous low noise audio segment; andoutputting the alternating video clips to create an audiovisual production containing video that alternates between two camera angles.
  • 13. The method of claim 9, further comprising the step of extracting content data from the first video input, the second video input, or the audio input to identify one or more switch-initiating events, wherein switching between the first video input and the second video input is only performed for low noise audio segments that follow switch-initiating events.
  • 14. The method of claim 13, wherein the content data is a keyword extracted using speech-to-text.
  • 15. The method of claim 9, wherein the audiovisual production comprises the first video input before the first low noise audio segment and during at least a portion of the first low noise audio segment, and the second video input during at least a portion of the first low noise audio segment and after the first low noise audio segment.
  • 16. The method of claim 9, further comprising: discarding at least a portion of the first video input, the second video input, and the audio input of the low noise audio event when the low noise audio event exceeds a predetermined length of time, such that the output audiovisual production is of shorter than the received video inputs and audio input.
  • 17. A system comprising: a first video input from a first video camera, a second video input from a second video camera, a third video input from a third video camera, wherein the first video camera, the second video camera, and the third video camera are directed towards a common area, such that the video cameras are configured to obtain video data of a common subject in the common area from different angles, wherein the first video input, second video input, and the third video input are recorded simultaneously and are synchronized;an audio input, wherein the audio input is recorded simultaneously and is synchronized with the first video input, the second video input, and the third video input;a non-transitory computer memory and a computer processor; and computer instructions stored on the memory for instructing the processor to perform the steps of: monitoring the audio input and the video inputs for switch-initiating events; andoutputting an audiovisual production;wherein the audiovisual production comprises: a first audiovisual clip, the first audiovisual clip comprising: a portion of the audio input occurring before a first switch-initiating event, anda portion of the first video input occurring before a first switch-initiating event, wherein the first audiovisual clip ends after a beginning of the first switch-initiating event;a second audiovisual clip, the second audiovisual clip comprising: a portion of the audio input occurring after the first switch-initiating event and before a second switch-initiating event, anda portion of the second video input occurring after the first switch-initiating event and before the second switch-initiating event, wherein the second audiovisual clip ends after a beginning of the second switch-initiating event; anda third audiovisual clip, the third audiovisual clip comprising: a portion of the audio input occurring after the second switch-initiating event, and(1) if the amount of time between the first switch-initiating event and the second switch-initiating event is greater than a switch delay time period, a portion of the third video input occurring immediately after an end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second switch-initiating event, or(2) if the amount of time between the first switch-initiating event and the second switch-initiating event is not greater than the switch delay time period, a portion of the second video input occurring immediately after the end of the second video input in the second audiovisual clip, the third audiovisual clip begins after the beginning of the second switch-initiating event.
  • 18. The system of claim 17, wherein the switch-initiating event comprises a keyword extracted from the audio input via speech-to-text.
  • 19. The system of claim 17, wherein the switch-initiating event comprises a length of time of at least 30 seconds since a most recent camera angle switch or a keyword extracted from the audio input via speech-to-text.
  • 20. The system of claim 17, wherein each video camera is directed towards a common area, such that each of the video cameras are configured to obtain video data of a common subject in the common area from different angles.
CLAIM OF PRIORITY

This application is a Continuation of U.S. patent application Ser. No. 16/910,986, filed Jun. 24, 2020, which is a Continuation of U.S. patent application Ser. No. 16/366,746, filed Mar. 27, 2019, the content of which is herein incorporated by reference in its entirety.

US Referenced Citations (449)
Number Name Date Kind
1173785 Deagan Feb 1916 A
1686351 Spitzglass Oct 1928 A
3152622 Rothermel Oct 1964 A
3764135 Madison Oct 1973 A
5109281 Kobori et al. Apr 1992 A
5410344 Graves et al. Apr 1995 A
5835667 Wactlar et al. Nov 1998 A
5867209 Irie et al. Feb 1999 A
5884004 Sato et al. Mar 1999 A
5886967 Aramaki Mar 1999 A
5897220 Huang et al. Apr 1999 A
5906372 Recard May 1999 A
5937138 Fukuda et al. Aug 1999 A
5949792 Yasuda et al. Sep 1999 A
6128414 Liu Oct 2000 A
6229904 Huang et al. May 2001 B1
6289165 Abecassis Sep 2001 B1
6484266 Kashiwagi et al. Nov 2002 B2
6502199 Kashiwagi et al. Dec 2002 B2
6504990 Abecassis Jan 2003 B1
RE37994 Fukuda et al. Feb 2003 E
6600874 Fujita et al. Jul 2003 B1
6618723 Smith Sep 2003 B1
6981000 Park et al. Dec 2005 B2
7095329 Saubolle Aug 2006 B2
7146627 Ismail et al. Dec 2006 B1
7293275 Krieger et al. Nov 2007 B1
7313539 Pappas et al. Dec 2007 B1
7336890 Lu et al. Feb 2008 B2
7499918 Ogikubo Mar 2009 B2
7606444 Erol et al. Oct 2009 B1
7650286 Obeid Jan 2010 B1
7702542 Aslanian Apr 2010 B2
7725812 Balkus et al. May 2010 B1
7797402 Roos Sep 2010 B2
7810117 Karnalkar et al. Oct 2010 B2
7865424 Pappas et al. Jan 2011 B2
7895620 Haberman et al. Feb 2011 B2
7904490 Ogikubo Mar 2011 B2
7962375 Pappas et al. Jun 2011 B2
7974443 Kipman et al. Jul 2011 B2
7991635 Hartmann Aug 2011 B2
7996292 Pappas et al. Aug 2011 B2
8032447 Pappas et al. Oct 2011 B2
8046814 Badenell Oct 2011 B1
8099415 Luo et al. Jan 2012 B2
8111326 Talwar Feb 2012 B1
8169548 Ryckman May 2012 B2
8185543 Choudhry et al. May 2012 B1
8205148 Sharpe Jun 2012 B1
8229841 Pappas et al. Jul 2012 B2
8238718 Toyama et al. Aug 2012 B2
8241628 Diefenbach-Streiber et al. Aug 2012 B2
8266068 Foss et al. Sep 2012 B1
8300785 White Oct 2012 B2
8301550 Pappas et al. Oct 2012 B2
8301790 Morrison et al. Oct 2012 B2
8326133 Lemmers Dec 2012 B2
8326853 Richard et al. Dec 2012 B2
8331457 Mizuno et al. Dec 2012 B2
8331760 Butcher Dec 2012 B2
8339500 Hattori et al. Dec 2012 B2
8358346 Hikita et al. Jan 2013 B2
8387094 Ho et al. Feb 2013 B1
8505054 Kirley Aug 2013 B1
8508572 Ryckman et al. Aug 2013 B2
8543450 Pappas et al. Sep 2013 B2
8560482 Miranda et al. Oct 2013 B2
8566880 Dunker et al. Oct 2013 B2
8600211 Nagano et al. Dec 2013 B2
8611422 Yagnik et al. Dec 2013 B1
8620771 Pappas et al. Dec 2013 B2
8633964 Zhu Jan 2014 B1
8650114 Pappas et al. Feb 2014 B2
8751231 Larsen et al. Jun 2014 B1
8774604 Torii et al. Jul 2014 B2
8792780 Hattori Jul 2014 B2
8818175 Dubin Aug 2014 B2
8824863 Kitamura et al. Sep 2014 B2
8854457 De Vleeschouwer et al. Oct 2014 B2
8856000 Larsen et al. Oct 2014 B1
8902282 Zhu Dec 2014 B1
8909542 Montero et al. Dec 2014 B2
8913103 Sargin Dec 2014 B1
8918532 Lueth et al. Dec 2014 B2
8930260 Pappas et al. Jan 2015 B2
8988528 Hikita Mar 2015 B2
9009045 Larsen et al. Apr 2015 B1
9015746 Holmdahl et al. Apr 2015 B2
9026471 Pappas et al. May 2015 B2
9026472 Pappas et al. May 2015 B2
9047634 Pappas et al. Jun 2015 B2
9064258 Pappas et al. Jun 2015 B2
9070150 Pappas et al. Jun 2015 B2
9092813 Pappas et al. Jul 2015 B2
9106804 Roberts Aug 2015 B2
9111579 Meaney et al. Aug 2015 B2
9117201 Kennell et al. Aug 2015 B2
9129640 Hamer Sep 2015 B2
9135674 Yagnik et al. Sep 2015 B1
9223781 Pearson et al. Dec 2015 B2
9224156 Moorer Dec 2015 B2
9305286 Larsen et al. Apr 2016 B2
9305287 Krishnamoorthy et al. Apr 2016 B2
9355151 Cranfill et al. May 2016 B1
9378486 Taylor et al. Jun 2016 B2
9398315 Oks et al. Jul 2016 B2
9402050 Recchia et al. Jul 2016 B1
9437247 Pendergast et al. Sep 2016 B2
9438934 Zhu Sep 2016 B1
9443556 Cordell et al. Sep 2016 B2
9456174 Boyle et al. Sep 2016 B2
9462301 Paśko Oct 2016 B2
9501663 Hopkins et al. Nov 2016 B1
9501944 Boneta et al. Nov 2016 B2
9542452 Ross et al. Jan 2017 B1
9544380 Deng et al. Jan 2017 B2
9554160 Han et al. Jan 2017 B2
9570107 Boiman et al. Feb 2017 B2
9583144 Ricciardi Feb 2017 B2
9600723 Pantofaru Mar 2017 B1
9607655 Bloch et al. Mar 2017 B2
9652745 Taylor et al. May 2017 B2
9653115 Bloch et al. May 2017 B2
9666194 Ondeck et al. May 2017 B2
9684435 Carr et al. Jun 2017 B2
9693019 Fluhr et al. Jun 2017 B1
9710790 Taylor et al. Jul 2017 B2
9723223 Banta et al. Aug 2017 B1
9747573 Shaburov et al. Aug 2017 B2
9792955 Fleischhauer et al. Oct 2017 B2
9805767 Strickland Oct 2017 B1
9823809 Roos Nov 2017 B2
9876963 Nakamura et al. Jan 2018 B2
9881647 McCauley et al. Jan 2018 B2
9936185 Delvaux et al. Apr 2018 B2
9940508 Kaps et al. Apr 2018 B2
9940973 Roberts et al. Apr 2018 B2
9979921 Holmes May 2018 B2
10008239 Eris Jun 2018 B2
10019653 Wilf et al. Jul 2018 B2
10021377 Newton et al. Jul 2018 B2
10108932 Sung et al. Oct 2018 B2
10115038 Hazur et al. Oct 2018 B2
10147460 Ullrich Dec 2018 B2
10152695 Chiu et al. Dec 2018 B1
10152696 Thankappan et al. Dec 2018 B2
10168866 Wakeen et al. Jan 2019 B2
10178427 Huang Jan 2019 B2
10235008 Lee et al. Mar 2019 B2
10242345 Taylor et al. Mar 2019 B2
10268736 Balasia et al. Apr 2019 B1
10296873 Balasia et al. May 2019 B1
10310361 Featherstone Jun 2019 B1
10318927 Champaneria Jun 2019 B2
10325243 Ross et al. Jun 2019 B1
10325517 Nielson et al. Jun 2019 B2
10331764 Rao et al. Jun 2019 B2
10346805 Taylor et al. Jul 2019 B2
10346928 Li et al. Jul 2019 B2
10353720 Wich-vila Jul 2019 B1
10433030 Packard et al. Oct 2019 B2
10438135 Larsen et al. Oct 2019 B2
10489439 Calapodescu et al. Nov 2019 B2
10607188 Kyllonen et al. Mar 2020 B2
10657498 Dey et al. May 2020 B2
10694097 Shirakyan Jun 2020 B1
10728443 Olshansky Jul 2020 B1
10735396 Krstic et al. Aug 2020 B2
10748118 Fang Aug 2020 B2
10796217 Wu Oct 2020 B2
10825480 Marco Nov 2020 B2
10963841 Olshansky Mar 2021 B2
11023735 Olshansky Jun 2021 B1
11127232 Olshansky Sep 2021 B2
11144882 Olshansky Oct 2021 B1
11184578 Olshansky Nov 2021 B2
11457140 Olshansky Sep 2022 B2
11636678 Olshansky Apr 2023 B2
11720859 Olshansky Aug 2023 B2
11783645 Olshanksy Oct 2023 B2
20010001160 Shoff et al. May 2001 A1
20010038746 Hughes et al. Nov 2001 A1
20020097984 Abecassis Jul 2002 A1
20020113879 Battle et al. Aug 2002 A1
20020122659 McGrath et al. Sep 2002 A1
20020191071 Rui et al. Dec 2002 A1
20030005429 Colsey Jan 2003 A1
20030027611 Recard Feb 2003 A1
20030189589 Leblanc et al. Oct 2003 A1
20030194211 Abecassis Oct 2003 A1
20040033061 Hughes et al. Feb 2004 A1
20040186743 Cordero Sep 2004 A1
20040264919 Taylor et al. Dec 2004 A1
20050095569 Franklin May 2005 A1
20050137896 Pentecost et al. Jun 2005 A1
20050187765 Kim et al. Aug 2005 A1
20050232462 Vallone et al. Oct 2005 A1
20050235033 Doherty Oct 2005 A1
20050271251 Russell et al. Dec 2005 A1
20060042483 Work et al. Mar 2006 A1
20060045179 Mizuno et al. Mar 2006 A1
20060100919 Levine May 2006 A1
20060116555 Pavlidis et al. Jun 2006 A1
20060229896 Rosen et al. Oct 2006 A1
20070088601 Money et al. Apr 2007 A1
20070124161 Mueller et al. May 2007 A1
20070237502 Ryckman et al. Oct 2007 A1
20070288245 Benjamin Dec 2007 A1
20080086504 Sanders et al. Apr 2008 A1
20080169929 Albertson et al. Jul 2008 A1
20090083103 Basser Mar 2009 A1
20090083670 Roos Mar 2009 A1
20090087161 Roberts Apr 2009 A1
20090144785 Walker et al. Jun 2009 A1
20090171899 Chittoor et al. Jul 2009 A1
20090248685 Pasqualoni et al. Oct 2009 A1
20090258334 Pyne Oct 2009 A1
20100086283 Ramachandran et al. Apr 2010 A1
20100143329 Larsen Jun 2010 A1
20100183280 Beauregard Jul 2010 A1
20100191561 Jeng et al. Jul 2010 A1
20100199228 Latta et al. Aug 2010 A1
20100223109 Hawn et al. Sep 2010 A1
20100325307 Roos Dec 2010 A1
20110055098 Stewart Mar 2011 A1
20110055930 Flake et al. Mar 2011 A1
20110060671 Erbey et al. Mar 2011 A1
20110076656 Scott et al. Mar 2011 A1
20110088081 Folkesson et al. Apr 2011 A1
20110135279 Leonard Jun 2011 A1
20120036127 Work et al. Feb 2012 A1
20120053996 Galbavy Mar 2012 A1
20120084649 Dowdell et al. Apr 2012 A1
20120114246 Weitzman May 2012 A1
20120130771 Kannan et al. May 2012 A1
20120257875 Sharpe Oct 2012 A1
20120271774 Clegg Oct 2012 A1
20130007670 Roos Jan 2013 A1
20130016815 Odinak et al. Jan 2013 A1
20130016816 Odinak et al. Jan 2013 A1
20130016823 Odinak et al. Jan 2013 A1
20130024105 Thomas Jan 2013 A1
20130111401 Newman et al. May 2013 A1
20130121668 Meaney et al. May 2013 A1
20130124998 Pendergast et al. May 2013 A1
20130124999 Agnoli et al. May 2013 A1
20130125000 Fleischhauer et al. May 2013 A1
20130176430 Zhu et al. Jul 2013 A1
20130177296 Geisner et al. Jul 2013 A1
20130212033 Work et al. Aug 2013 A1
20130212180 Work et al. Aug 2013 A1
20130216206 Dubin Aug 2013 A1
20130218688 Roos Aug 2013 A1
20130222601 Engstroem et al. Aug 2013 A1
20130226578 Bolton et al. Aug 2013 A1
20130226674 Field et al. Aug 2013 A1
20130226910 Work et al. Aug 2013 A1
20130254192 Work et al. Sep 2013 A1
20130259447 Sathish et al. Oct 2013 A1
20130266925 Nunamaker et al. Oct 2013 A1
20130268452 MacEwen et al. Oct 2013 A1
20130283378 Costigan et al. Oct 2013 A1
20130290210 Cline et al. Oct 2013 A1
20130290325 Work et al. Oct 2013 A1
20130290420 Work et al. Oct 2013 A1
20130290448 Work et al. Oct 2013 A1
20130297589 Work et al. Nov 2013 A1
20130332381 Clark et al. Dec 2013 A1
20130332382 Lapasta et al. Dec 2013 A1
20140036023 Croen et al. Feb 2014 A1
20140089217 McGovern et al. Mar 2014 A1
20140092254 Mughal et al. Apr 2014 A1
20140123177 Kim et al. May 2014 A1
20140125703 Roveta et al. May 2014 A1
20140143165 Posse et al. May 2014 A1
20140153902 Pearson et al. Jun 2014 A1
20140186004 Hamer Jul 2014 A1
20140191939 Penn et al. Jul 2014 A1
20140192200 Zagron Jul 2014 A1
20140198196 Howard et al. Jul 2014 A1
20140214703 Moody Jul 2014 A1
20140214709 Greaney Jul 2014 A1
20140245146 Roos Aug 2014 A1
20140258288 Work et al. Sep 2014 A1
20140270706 Pasko Sep 2014 A1
20140278506 Rogers et al. Sep 2014 A1
20140278683 Kennell et al. Sep 2014 A1
20140279634 Seeker Sep 2014 A1
20140282709 Hardy et al. Sep 2014 A1
20140317009 Bilodeau et al. Oct 2014 A1
20140317126 Work et al. Oct 2014 A1
20140325359 Vehovsky et al. Oct 2014 A1
20140325373 Kramer et al. Oct 2014 A1
20140327779 Eronen et al. Nov 2014 A1
20140330734 Sung et al. Nov 2014 A1
20140334670 Guigues et al. Nov 2014 A1
20140336942 Pe'Er et al. Nov 2014 A1
20140337900 Hurley Nov 2014 A1
20140356822 Hoque et al. Dec 2014 A1
20140358810 Hardtke et al. Dec 2014 A1
20140359439 Lyren Dec 2014 A1
20150003603 Odinak et al. Jan 2015 A1
20150003605 Odinak et al. Jan 2015 A1
20150006422 Carter et al. Jan 2015 A1
20150012453 Odinak et al. Jan 2015 A1
20150046357 Danson et al. Feb 2015 A1
20150063775 Nakamura et al. Mar 2015 A1
20150067723 Bloch et al. Mar 2015 A1
20150099255 Sinem Aslan et al. Apr 2015 A1
20150100702 Krishna et al. Apr 2015 A1
20150127565 Chevalier et al. May 2015 A1
20150139601 Mate et al. May 2015 A1
20150154564 Moon et al. Jun 2015 A1
20150155001 Kikugawa et al. Jun 2015 A1
20150170303 Geritz et al. Jun 2015 A1
20150199646 Taylor et al. Jul 2015 A1
20150201134 Carr et al. Jul 2015 A1
20150205800 Work et al. Jul 2015 A1
20150205872 Work et al. Jul 2015 A1
20150206102 Cama et al. Jul 2015 A1
20150206103 Larsen et al. Jul 2015 A1
20150222815 Wang et al. Aug 2015 A1
20150228306 Roberts et al. Aug 2015 A1
20150242707 Wilf et al. Aug 2015 A1
20150269165 Work et al. Sep 2015 A1
20150269529 Kyllonen et al. Sep 2015 A1
20150269530 Work et al. Sep 2015 A1
20150271289 Work et al. Sep 2015 A1
20150278223 Work et al. Oct 2015 A1
20150278290 Work et al. Oct 2015 A1
20150278964 Work et al. Oct 2015 A1
20150302158 Morris et al. Oct 2015 A1
20150324698 Karaoguz et al. Nov 2015 A1
20150339939 Gustafson et al. Nov 2015 A1
20150356512 Bradley Dec 2015 A1
20150380052 Hamer Dec 2015 A1
20160005029 Ivey et al. Jan 2016 A1
20160036976 Odinak et al. Feb 2016 A1
20160104096 Ovick et al. Apr 2016 A1
20160116827 Tarres Bolos Apr 2016 A1
20160117942 Marino et al. Apr 2016 A1
20160139562 Crowder et al. May 2016 A1
20160154883 Boerner Jun 2016 A1
20160155475 Hamer Jun 2016 A1
20160180234 Siebach et al. Jun 2016 A1
20160180883 Hamer Jun 2016 A1
20160219264 Delvaux et al. Jul 2016 A1
20160225409 Eris Aug 2016 A1
20160225410 Lee et al. Aug 2016 A1
20160247537 Ricciardi Aug 2016 A1
20160267436 Silber et al. Sep 2016 A1
20160313892 Roos Oct 2016 A1
20160323608 Bloch et al. Nov 2016 A1
20160330398 Recchia et al. Nov 2016 A1
20160364692 Bhaskaran et al. Dec 2016 A1
20170024614 Sanil et al. Jan 2017 A1
20170026667 Pasko Jan 2017 A1
20170039525 Seidle et al. Feb 2017 A1
20170076751 Hamer Mar 2017 A9
20170134776 Ranjeet et al. May 2017 A1
20170148488 Li et al. May 2017 A1
20170164013 Abramov et al. Jun 2017 A1
20170164014 Abramov et al. Jun 2017 A1
20170164015 Abramov et al. Jun 2017 A1
20170171602 Qu Jun 2017 A1
20170178688 Ricciardi Jun 2017 A1
20170195491 Odinak et al. Jul 2017 A1
20170206504 Taylor et al. Jul 2017 A1
20170213190 Hazan Jul 2017 A1
20170213573 Takeshita et al. Jul 2017 A1
20170227353 Brunner Aug 2017 A1
20170236073 Borisyuk et al. Aug 2017 A1
20170244894 Aggarwal et al. Aug 2017 A1
20170244984 Aggarwal et al. Aug 2017 A1
20170244991 Aggarwal et al. Aug 2017 A1
20170262706 Sun et al. Sep 2017 A1
20170264958 Hutten Sep 2017 A1
20170293413 Matsushita et al. Oct 2017 A1
20170316806 Warren et al. Nov 2017 A1
20170332044 Marlow et al. Nov 2017 A1
20170353769 Husain et al. Dec 2017 A1
20170372748 McCauley et al. Dec 2017 A1
20180011621 Roos Jan 2018 A1
20180025303 Janz Jan 2018 A1
20180054641 Hall et al. Feb 2018 A1
20180070045 Holmes Mar 2018 A1
20180074681 Roos Mar 2018 A1
20180082238 Shani Mar 2018 A1
20180096307 Fortier et al. Apr 2018 A1
20180109737 Nakamura et al. Apr 2018 A1
20180109826 McCoy et al. Apr 2018 A1
20180110460 Danson et al. Apr 2018 A1
20180114154 Bae Apr 2018 A1
20180130497 McCauley et al. May 2018 A1
20180132014 Khazanov et al. May 2018 A1
20180150604 Arena et al. May 2018 A1
20180158027 Venigalla Jun 2018 A1
20180182436 Ullrich Jun 2018 A1
20180191955 Aoki et al. Jul 2018 A1
20180218238 Viirre et al. Aug 2018 A1
20180226102 Roberts et al. Aug 2018 A1
20180227501 King Aug 2018 A1
20180232751 Terhark et al. Aug 2018 A1
20180247271 Van Hoang et al. Aug 2018 A1
20180253697 Sung et al. Sep 2018 A1
20180268868 Salokannel et al. Sep 2018 A1
20180270613 Park Sep 2018 A1
20180277093 Carr et al. Sep 2018 A1
20180295428 Bi et al. Oct 2018 A1
20180302680 Cormican Oct 2018 A1
20180308521 Iwamoto Oct 2018 A1
20180316947 Todd Nov 2018 A1
20180336528 Carpenter et al. Nov 2018 A1
20180336930 Takahashi Nov 2018 A1
20180350405 Marco Dec 2018 A1
20180353769 Smith et al. Dec 2018 A1
20180374251 Mitchell et al. Dec 2018 A1
20180376225 Jones et al. Dec 2018 A1
20190005373 Nims et al. Jan 2019 A1
20190019157 Saha et al. Jan 2019 A1
20190057356 Larsen et al. Feb 2019 A1
20190087558 Mercury et al. Mar 2019 A1
20190096307 Liang et al. Mar 2019 A1
20190141033 Kaafar et al. May 2019 A1
20190220824 Liu Jul 2019 A1
20190244176 Chuang et al. Aug 2019 A1
20190259002 Balasia et al. Aug 2019 A1
20190295040 Clines Sep 2019 A1
20190311488 Sareen Oct 2019 A1
20190325064 Mathiesen et al. Oct 2019 A1
20200012350 Tay Jan 2020 A1
20200110786 Kim Apr 2020 A1
20200126545 Kakkar et al. Apr 2020 A1
20200143329 Gamaliel May 2020 A1
20200197793 Yeh et al. Jun 2020 A1
20200311163 Ma et al. Oct 2020 A1
20200311682 Olshansky Oct 2020 A1
20200311953 Olshansky Oct 2020 A1
20200396376 Olshansky Dec 2020 A1
20210035047 Mossoba et al. Feb 2021 A1
20210158663 Buchholz et al. May 2021 A1
20210174308 Olshansky Jun 2021 A1
20210233262 Olshansky Jul 2021 A1
20210312184 Olshansky Oct 2021 A1
20210314521 Olshansky Oct 2021 A1
20220005295 Olshansky Jan 2022 A1
20220019806 Olshansky Jan 2022 A1
20220092548 Olshansky Mar 2022 A1
Foreign Referenced Citations (85)
Number Date Country
2002310201 Mar 2003 AU
2007249205 Mar 2013 AU
2206105 Dec 2000 CA
2763634 Dec 2012 CA
109146430 Jan 2019 CN
1376584 Jan 2004 EP
1566748 Aug 2005 EP
1775949 Dec 2007 EP
1954041 Aug 2008 EP
2009258175 Nov 2009 JP
2019016192 Jan 2019 JP
9703366 Jan 1997 WO
9713366 Apr 1997 WO
9713367 Apr 1997 WO
9828908 Jul 1998 WO
9841978 Sep 1998 WO
9905865 Feb 1999 WO
0133421 May 2001 WO
0117250 Sep 2002 WO
03003725 Jan 2003 WO
2004062563 Jul 2004 WO
2005114377 Dec 2005 WO
2006103578 Oct 2006 WO
2006129496 Dec 2006 WO
2007039994 Apr 2007 WO
2007097218 Aug 2007 WO
2008029803 Mar 2008 WO
2008039407 Apr 2008 WO
2009042858 Apr 2009 WO
2009042900 Apr 2009 WO
2009075190 Jun 2009 WO
2009116955 Sep 2009 WO
2009157446 Dec 2009 WO
2010055624 May 2010 WO
2010116998 Oct 2010 WO
2011001180 Jan 2011 WO
2011007011 Jan 2011 WO
2011035419 Mar 2011 WO
2011129578 Oct 2011 WO
2011136571 Nov 2011 WO
2012002896 Jan 2012 WO
2012068433 May 2012 WO
2012039959 Jun 2012 WO
2012089855 Jul 2012 WO
2013026095 Feb 2013 WO
2013039351 Mar 2013 WO
2013074207 May 2013 WO
2013088208 Jun 2013 WO
2013093176 Jun 2013 WO
2013131134 Sep 2013 WO
2013165923 Nov 2013 WO
2014089362 Jun 2014 WO
2014093668 Jun 2014 WO
2014152021 Sep 2014 WO
2014153665 Oct 2014 WO
2014163283 Oct 2014 WO
2014164549 Oct 2014 WO
2015031946 Apr 2015 WO
2015071490 May 2015 WO
2015109290 Jul 2015 WO
2016031431 Mar 2016 WO
2016053522 Apr 2016 WO
2016073206 May 2016 WO
2016123057 Aug 2016 WO
2016138121 Sep 2016 WO
2016138161 Sep 2016 WO
2016186798 Nov 2016 WO
2016189348 Dec 2016 WO
2017022641 Feb 2017 WO
2017042831 Mar 2017 WO
2017049612 Mar 2017 WO
2017051063 Mar 2017 WO
2017096271 Jun 2017 WO
2017130810 Aug 2017 WO
2017150772 Sep 2017 WO
2017192125 Nov 2017 WO
2018042175 Mar 2018 WO
2018094443 May 2018 WO
2019226051 Nov 2019 WO
2020198230 Oct 2020 WO
2020198240 Oct 2020 WO
2020198363 Oct 2020 WO
2021108564 Jun 2021 WO
2021202293 Oct 2021 WO
2021202300 Oct 2021 WO
Non-Patent Literature Citations (89)
Entry
“International Preliminary Report on Patentability,” for PCT Application No. PCT/US2021/024450 dated Oct. 13, 2022 (11 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/486,489 dated Oct. 20, 2022 (56 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 17/490,713, filed Nov. 15, 2022 (8 pages).
Dragsnes, Steinar J. “Development of a Synchronous, Distributed and Agent-Supported Framework: Exemplified by a Mind Map Application,” MS Thesis; The University of Bergen, 2003 (156 pages).
Rizzo, Albert, et al. “Detection and Computational Analysis of Psychological Signals Using a Virtual Human Interviewing Agent,” Journal of Pain Management 9.3 (2016):311-321 (10 pages).
Sen, Taylan, et al. “Automated Dyadic Data Recorder (ADDR) Framework and Analysis of Facial Cues in Deceptive Communication,” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1.4 (2018): 1-22 (11 pages).
“Air Canada Keeping Your Points Active Aeroplan,” https://www.aircanada.com/us/en/aco/home/aeroplan/your-aeroplan/inactivity-policy.html, 6 pages.
“American Express Frequently Asked Question: Why were Membership Rewards points forfeited and how can I reinstate them?”, https://www.americanexpress.com/us/customer-service/faq.membership-rewards-points-forfeiture.html, 2 pages.
“DaXtra Parser (CVX) Technical Specifications,” DaXtra Parser Spec. available at URL: <https://cvxdemo.daxtra.com/cvx/download/Parser%20Technical%20Specifications.pdf> at least as early as Feb. 25, 2021 (3 pages).
“Final Office Action,” for U.S. Appl. No. 16/366,703 dated Nov. 19, 2019 (25 pages).
“Final Office Action,” for U.S. Appl. No. 16/696,781 dated Oct. 8, 2020 (26 pages).
“Final Office Action,” for U.S. Appl. No. 16/828,578 dated Jan. 14, 2021 (27 pages).
“Final Office Action,” for U.S. Appl. No. 16/910,986 dated Jan. 25, 2022 (40 pages).
“Final Office Action,” for U.S. Appl. No. 17/230,692 dated Aug. 24, 2022 (31 pages).
“International Preliminary Report on Patentability,” for PCT Application No. PCT/US2020/024470 dated Oct. 7, 2021 (9 pages).
“International Preliminary Report on Patentability,” for PCT Application No. PCT/US2020/024488 dated Oct. 7, 2021 (9 pages).
“International Preliminary Report on Patentability,” for PCT Application No. PCT/US2020/024722 dated Oct. 7, 2021 (8 pages).
“International Preliminary Report on Patentability,” for PCT Application No. PCT/US2020/062246 dated Jun. 9, 2022 (12 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2020/024470 dated Jul. 9, 2020 (13 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2020/024488 dated May 19, 2020 (14 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2020/024722 dated Jul. 10, 2020 (13 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2020/062246 dated Apr. 1, 2021 (18 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2021/024423 dated Jun. 16, 2021 (13 pages).
“International Search Report and Written Opinion,” for PCT Application No. PCT/US2021/024450 dated Jun. 4, 2021 (14 pages).
“Invitation to Pay Additional Fees,” for PCT Application No. PCT/US2020/062246 dated Feb. 11, 2021 (14 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/366,703 dated Jun. 10, 2019 (28 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/366,703 dated May 6, 2020 (65 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/366,746 dated Aug. 22, 2019 (53 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/696,781 dated Apr. 7, 2020 (43 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/696,781 dated Jan. 26, 2021 (28 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/828,578 dated Sep. 24, 2020 (39 pages).
“Non-Final Office Action,” for U.S. Appl. No. 16/910,986 dated Jun. 23, 2021 (70 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/025,902 dated Jan. 29, 2021 (59 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/180,381 dated Sep. 19, 2022 (64 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/230,692 dated Feb. 15, 2022 (58 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/490,713 dated Aug. 16, 2022 (41 pages).
“Notice of Allowance,” for U.S. Appl. No. 16/366,703 dated Nov. 18, 2020 (19 pages).
“Notice of Allowance,” for U.S. Appl. No. 16/366,746 dated Mar. 12, 2020 (40 pages).
“Notice of Allowance,” for U.S. Appl. No. 16/696,781 dated May 17, 2021 (20 pages).
“Notice of Allowance,” for U.S. Appl. No. 16/910,986 dated May 20, 2022 (17 pages).
“Notice of Allowance,” for U.S. Appl. No. 16/931,964 dated Feb. 2, 2021 (42 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/025,902 dated May 11, 2021 (20 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/212,688 dated Jun. 9, 2021 (39 pages).
“Nurse Resumes,” Post Job Free Resume Search Results for “nurse” available at URL <https://www.postjobfree.com/resumes?q=nurse&l=&radius=25> at least as early as Jan. 26, 2021 (2 pages).
“Nurse,” LiveCareer Resume Search results available online at URL <https://www.livecareer.com/resume-search/search?jt=nurse> website published as early as Dec. 21, 2017 (4 pages).
“Response to Advisory Action,” for U.S. Appl. No. 16/696,781, filed Jan. 8, 2021 (22 pages).
“Response to Final Office Action,” for U.S. Appl. No. 16/366,703, filed Feb. 18, 2020 (19 pages).
“Response to Final Office Action,” for U.S. Appl. No. 16/696,781, filed Dec. 8, 2020 (18 pages).
“Response to Final Office Action,” for U.S. Appl. No. 16/910,986, filed Apr. 20, 2022 (13 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 16/366,746, filed Nov. 21, 2019 (12 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 16/696,781, filed Apr. 23, 2021 (16 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 16/696,781, filed Jul. 6, 2020 (14 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 16/828,578, filed Dec. 22, 2020 (17 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 16/910,986, filed Sep. 30, 2021 (18 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 17/025,902, filed Apr. 28, 2021 (16 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 17/230,692, filed Jun. 14, 2022 (15 pages).
“Response to Non-Final Rejection,” dated May 6, 2020 for U.S. Appl. No. 16/366,703, submitted via EFS-Web on Sep. 8, 2020, 25 pages.
“Resume Database,” Mighty Recruiter Resume Database available online at URL <https://www.mightyrecruiter.com/features/resume-database> at least as early as Sep. 4, 2017 (6 pages).
“Resume Library,” Online job board available at Resume-library.com at least as early as Aug. 6, 2019 (6 pages).
“Television Studio,” Wikipedia, Published Mar. 8, 2019 and retrieved May 27, 2021 from URL <https://en.wikipedia.org/w/index/php?title=Television_studio&oldid=886710983> (3 pages).
“Understanding Multi-Dimensionality in Vector Space Modeling,” Pythonic Excursions article published Apr. 16, 2019, accessible at URL <https://aegis4048.github.io/understanding_multi-dimensionality_in_vector_space_modeling> (29 pages).
Advantage Video Systems “Jeffrey Stansfield of AVS interviews rep about Air-Hush products at the 2019 NAMM Expo,” YouTube video, available at https://www.youtube.com/watch?v=nWzrM99qk_o, accessed Jan. 17, 2021.
Alley, E. “Professional Autonomy in Video Relay Service Interpreting: Perceptions of American Sign Language-English Interpreters,” (Order No. 10304259). Available from ProQuest Dissertations and Theses Professional. (Year: 2016), 209 pages.
Bishop, Todd “Microsoft patents tech to score meetings using body language, facial expressions, other data,” Article published Nov. 28, 2020 at URL <https://www.geekwire.com/author/todd/> (7 pages).
Brocardo, Marcelo Luiz, et al.“Verifying Online User Identity using Stylometric Analysis for Short Messages,” Journal of Networks, vol. 9, No. 12, Dec. 2014, pp. 3347-3355.
Hughes, K. “Corporate Channels: How American Business and Industry Made Television Useful,” (Order No. 10186420). Available from ProQuest Dissertations and Theses Professional. (Year: 2015), 499 pages.
Jakubowski, Kelly, et al.“Extracting Coarse Body Movements from Video in Music Performance: A Comparison of Automated Computer Vision Techniques with Motion Capture Data,” Front. Digit. Humanit. 2017, 4:9 (8 pages).
Johnston, A. M, et al.“A Mediated Discourse Analysis of Immigration Gatekeeping Interviews,” (Order No. 3093235). Available from ProQuest Dissertations and Theses Professional (Year: 2003), 262 pages.
Lai, Kenneth, et al.“Decision Support for Video-based Detection of Flu Symptoms,” Biometric Technologies Laboratory, Department of Electrical and Computer Engineering, University of Calgary, Canada, Aug. 24, 2020, available at URL <https://ucalgary.ca/labs/biometric-technologies/publications> (8 pages).
Liu, Weihua, et al.“RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System,” Mathematical Problems in Engineering vol. 2015, article ID 863732 (16 pages).
Luenendonk, Martin “The Secrets to Interviewing for a Role That's Slightly Out of Reach,” Cleverism Article available at URL <https://www.cleverism.com/interviewing-for-a-role-thats-slightly-out-of-reach/> last updated Sep. 25, 2019 (13 pages).
Pentland, S. J.“Human-Analytics in Information Systems Research and Applications in Personnel Selection,” (Order No. 10829600). Available from ProQuest Dissertations and Theses Professional. (Year: 2018), 158 pages.
Ramanarayanan, Vikram, et al.“Evaluating Speech, Face, Emotion and Body Movement Time-series Features for Automated Multimodal Presentation Scoring,” In Proceedings of the 2015 ACM on (ICMI 2015). Association for Computing Machinery, New York, NY, USA, 23-30 (8 pages).
Randhavane, Tanmay, et al.“Identifying Emotions from Walking Using Affective and Deep Features,” Jan. 9, 2020, Article available at Cornell University website URL <https://arxiv.org/abs/1906.11884v4> (15 pages).
Swanepoel, De Wet, et al.“A Systematic Review of Telehealth Applications in Audiology,” Telemedicine and e-Health 16.2 (2010): 181-200 (20 pages).
Wang, Jenny “How to Build a Resume Recommender like the Applicant Tracking System (ATS),” Towards Data Science article published Jun. 25, 2020, accessible at URL <https://towardsdatascience.com/resume-screening-tool-resume-recommendation-engine-in-a-nutshell-53fcf6e6559b> (14 pages).
Yun, Jaeseok, et al.“Human Movement Detection and Identification Using Pyroelectric Infrared Sensors,” Sensors 2014, 14, 8057-8081 (25 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/318,774 dated Apr. 5, 2023 (60 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/476,014 dated Apr. 28, 2023 (10 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/486,489, dated Mar. 17, 2023 (18 pages).
“Response to Final Office Action,” for U.S. Appl. No. 17/180,381, filed Apr. 24, 2023 (15 pages).
“Response to Non Final Office Action,” for U.S. Appl. No. 17/476,014, filed Apr. 18, 2023 (16 pages).
“Final Office Action,” for U.S. Appl. No. 17/180,381 dated Jan. 23, 2023 (25 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/476,014 dated Jan. 18, 2023 (62 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/490,713 dated Dec. 6, 2022 (9 pages).
“Response to Non-Final Office Action,” for U.S. Appl. No. 17/180,381, filed Dec. 15, 2022, 2022 (13 pages).
“Response to Non-Final Office Action,” for U.S. Appl. No. 17/486,489, filed Jan. 18, 2023 (11 pages).
“Non-Final Office Action,” for U.S. Appl. No. 17/180,381 dated Jul. 14, 2023 (15 pages).
“Notice of Allowance,” for U.S. Appl. No. 17/318,774 dated Aug. 16, 2023 (11 pages).
Related Publications (1)
Number Date Country
20230091194 A1 Mar 2023 US
Continuations (2)
Number Date Country
Parent 16910986 Jun 2020 US
Child 17951633 US
Parent 16366746 Mar 2019 US
Child 16910986 US