Patent Grant
7089575
1. Field of the Invention
The present invention is directed to identifying and learning commercials during a program such as a broadcast television program, and more specifically to identifying and learning commercials during a broadcast television program using transcript information.
2. Description of the Related Art
Television viewing systems are available which automatically detect selected segments of a television signal such as commercial advertisements or undesired portions of the program. These commercial detection systems are typically used to mute the audio portion of the television broadcast when the undesired portion of the program appears, or for controlling a video player to skip the undesired portion of the program during recording or replay. Although a wide variety of techniques have been developed for detecting selected segments of television programs, none of the prior art systems monitor the transcript information (e.g., closed-captioned signal) of a television program to identify and learn the commercial portions which occur during the program. In addition, none of the prior art systems identify, segment and store individual commercials which occur during a commercial segment of the program for later use, for example, to create a library of commercials to identify corresponding commercial portions of subsequent television broadcasts.
It is therefore an object of the present invention to provide a method which identifies and learns commercial portions of a broadcast program.
It is another object of the present invention to provide a method which monitors the transcript information corresponding to a broadcast program to identify and learn commercial portions of the broadcast program.
It is a further object of the present invention to provide a method which identifies, segments and learns individual commercials which are broadcast during a commercial segment of a broadcast program by analyzing the transcript information associated therewith.
It is a further object of the present invention to provide a method for identifying and learning commercial portions of a broadcast program which overcome inherent disadvantages of known commercial detection methods.
In accordance with one form of the present invention, a method of identifying commercial segments during a program includes the steps of using transcript information associated with the program, detecting “non-stop” words in the transcript information during a first time period which occur more than a predetermined number of times, detecting “non-stop” words in the transcript information during a second time period which occur more than a predetermined number of times, and comparing the non-stop words detected during the first time period and the “non-stop” words detected during the second time period.
In accordance with another form of the present invention, a method of learning and storing commercial segments which occur during a program includes the steps of identifying a possible commercial segment which occurs during the program, comparing “non-stop” words of the possible commercial segment with “non-stop” words of each of a list of probable commercial segments previously identified to determine at least one matching probable commercial segment, comparing transcript text of the possible commercial segment with transcript text of the at least one matching probable commercial segment, storing the transcript text which is common to both the possible commercial segment and the at least one matching probable commercial segment, removing the at least one matching stored probable commercial segment from the list of probable commercial segments, and adding the at least one matching probable commercial segment to a list of candidate commercial segments.
In accordance with another form of the present invention, a method of learning and storing commercial segments which occur during a program includes the steps of identifying a possible commercial segment which occurs during the program, comparing “non-stop” words of the possible commercial segment with “non-stop” words of each of a list of candidate commercial segments previously identified to determine at least one matching candidate commercial segment, comparing transcript text of the possible commercial segment with transcript text of the at least one matching candidate commercial segment, storing the transcript text which is common to both the possible commercial segment and the at least one matching candidate commercial segment, removing the at least one matching candidate commercial segment from the list of candidate commercial segments, and adding the at least one matching candidate commercial segment to a list of found commercial segments.
In accordance with another form of the present invention, a method of learning and storing commercial segments which occur during a program includes the steps of identifying a possible commercial segment which occurs during the program, comparing “non-stop” words of the possible commercial segment with “non-stop” words of each of a list of found commercial segments previously identified to determine at least one matching found commercial segment, comparing the transcript text of the possible commercial segment with transcript text of the at least one matching found commercial segment, storing the transcript text which is common to both the possible commercial segment and the at least one matching found commercial segment, and incrementing a counter which indicates the frequency of occurrence of the at least one matching found commercial segment. The method also includes adding the found commercial segment to a found commercial list.
In accordance with another form of the present invention, a method of retrieving a stored commercial segment includes the steps of identifying at least one non-stop word indicative of a commercial segment which is desired, identifying stored commercial segments which correspond to the identified non-stop word, and outputting the identified stored commercial segments which correspond to the identified non-stop words. The method further includes marking the identified stored commercial segment as a commercial area.
The above and other objects, features and advantages of the present invention will become readily apparent from the following detailed description thereof, which is to be read in connection with the accompanying drawing.
Referring now to the drawings, the method for using transcript information to identify and learn commercial portions of a program is shown. The term transcript information is intended to indicate text, for example, closed-captioned text, which is typically provided with a video program's transmission (audio/data/video) signal and which corresponds to the spoken and non-spoken events of the video program or other textual source like EPG (electronic programming guide) data. The transcript information can be obtained from video text or screen text (e.g., by detecting the subtitles of the video) and by applying optical character recognition (OCR) on the extracted text such as that disclosed in U.S. Ser. No. 09/441,943 entitled “Video Stream Classification Symbol Isolation Method and System” filed Nov. 17, 1999, and U.S. Ser. No. 09/441,949 entitled “Symbol Classification with Shape Features Applied to a Neural Network” filed Nov. 17, 1999, the entire disclosures of each of which are incorporated herein by reference.
If the audio/data/video signal does not include a text portion (i.e., it does not include transcript information), transcript information can be generated using techniques such as speech-to-text conversion (if subtitles exist, subtitle recognition using OCR is employed to generate transcript information) as known in the art. The transcript information may also be obtained from a third party source, for example, TV Guide via the internet.
The present invention is based on the knowledge that the transcript information of a program is capable of being analyzed and searched using known searching techniques such as key-word searching and statistical text indexing and retrieval. Generally, the method for commercial segment identification includes analyzing the transcript information corresponding to a program (audio, video, data and the like) and determining the beginning of a commercial portion of the program (or the end of a non-commercial portion of the program by identifying “going into commercial” cues in the transcript information as explained in more detail below). Once the beginning of a commercial portion of the program has been identified, the method analyzes the transcript information to separately identify individual commercials contained within the identified commercial portion of the program. The signatures of individually identified commercials are then compared to previously identified signatures (previously stored) of commercial segments, stored as separate entities in a database, to identify specific commercial portions of the commercial segment. Once the commercial segments have been stored in the database, the user can access the database to search for a particular commercial. Alternative to the foregoing, any standard commercial detection technique based on audio/video characteristics can be used to tentatively determine commercial areas, such as those disclosed in U.S. Ser. No. 09/417,288 filed Oct. 13, 1999 entitled Automatic Signature-Base Spotting, Learning and Extracting of Commercials and Other Video Content by Dimitrova, McGee, and Agnihotri, and U.S. Ser. No. 09/123,444 filed Jul. 28, 1998 entitled Apparatus and Method for Locating a Commercial Disposed Within a Video Data Stream by Dimitrova, McGee, Elenbaas, Leyvi, Ramsey and Berkowitz, the entire disclosures of which are incorporated by reference.
Referring initially to
If the program signal does contain transcript information for the entertainment and the commercial portions of the program (Yes in Step 10), the transcript information is extracted from the program signal (Step 16). The EPG data signal is then analyzed to determine the type of program (Step 20) (e.g., talk show, news program, etc). Other program type determining methods can be employed such as those which analyze the transcript information for cues as to the program type such as those disclosed in U.S. Ser. No. 09/739,476 filed Dec. 18, 2000 entitled Apparatus and Method of Program Classification Using Observed Cues in the Transcript Information, by Kavitha Devara, and U.S. Ser. No. 09/712,681 filed Nov. 14, 2000 entitled Method and Apparatus for the Summarization and Indexing of Video Programs Using Transcript Information, by Lalitha Agnihotri, Kavitha Devara and Nevenka Dimitrova, the entire disclosures of which are incorporated herein by reference.
If the EPG data indicates that the program is of the type which would provide cues in the spoken text as to the occurrence of a commercial (such as a news program or a talk show), this fact is noted (Step 22). News programs and talk shows provide cues as to the occurrence of commercials (called “going into commercial” cues) with phrases such as “when we come back”, “still ahead”, “after these messages”, “after the commercial break”, and “up next”. When these phrases are identified in the transcript information, there is a high degree of certainty that a commercial segment is soon to follow. If the program is a talk show or news program (Yes in Step 22), the transcript information is monitored for the occurrence of the commercial cues (Step 24). When a commercial cue is detected, the region is marked as the beginning of a commercial segment of the program (Step 26). Thereafter, the transcript information is monitored for a first time period (Step 28) for “non-stop” words which occur above a predetermined threshold (Step 30). It should be noted that news programs and talk shows also provide cues in the text as to a return from a commercial break to regular programming when the host of the news program or talk show says things like “welcome back”. When such a phrase is identified in the transcript information, there is a high degree of certainty that a commercial segment has ended.
Non-stop words are words other than “an”, “the”, “of”, etc. The inventors have recognized that advertisers desire to deliver their message in a very short period of time. We can have recognition of brand names/database aids in labeling commercials. This leads to the product name, company name and other identifying features being repeated frequently during a commercial segment. If non-stop words (common to a product being advertised) appear numerous times during a relatively short time period during the program, this is indicative of a commercial. In one embodiment the time period is about 15 seconds and the method determines whether non-stop words are mentioned more than once during the time period. If non-stop words above the predetermined threshold are identified in Step 30 (X>1 in Step 30), the transcript text is monitored for a second time period (which preferably overlaps with the prior time period) and the non-stop words which occur more than the predetermined number of times in the second time period are noted (Step 32). If at least one non-stop word occurs more than a predetermined number of times (X>1 in Step 32), then a determination is made as to whether the non-stop words of the current time period coincide with the non-stop words of prior time periods (Step 36).
If the non-stop words identified in the current time period and the prior time period do not coincide (i.e., they do not have at least one common non-stop word) (NO in Step 36), then the current and prior time periods are not part of the same commercial segment (Step 38) and the start of the current time period is marked as the start of a new commercial segment (Step 40). Thereafter, the transcript information is monitored for a next time period which overlaps with at least the prior time period and the non-stop words which occur more than a predetermined number of times above a threshold are noted (Step 42).
If in Step 42 non-stop words are identified which occur more than a predetermined number of times (X>1 in Step 42), a determination is made as to whether the non-stop words of the current time period coincide with the non-stop words of prior time periods (Step 46). If the non-stop words of the current time period coincide with non-stop words of a prior time period (YES in Step 46), then a notation is made that the current time period is part of the same commercial as the prior time period (Step 48). Thereafter, a determination is made as to whether the current transcript information corresponds to a return to the non-commercial portion of the program (Step 50). If it is determined that the current transcript information corresponds to a return to the non-commercial portion of the program (YES in Step 50) (e.g., the host of the show says “Welcome back”), the method returns to Step 24. However, if it is determined that the current transcript information is not indicative of a return to the non-commercial portion of the program (NO in Step 50), then the method returns to Step 32 to monitor the transcript information for a new time period.
If in Step 36 it is determined that the non-stop words of the current time period coincide with non-stop words of a prior time period (YES in Step 36), then it is determined that the prior time period and the current time period are part of the same commercial segment (Step 52). Thereafter, the transcript information is monitored for a next time period which preferably overlaps with at least the prior time period. The non-stop words which occur more than a predetermined number of times are noted (Step 54).
If the non-stop words occur more than a predetermined number of times in the current time period (X>1 in Step 54), a determination is made as to whether the non-stop words of the current time period coincide with the non-stop words of the prior time periods (Step 58). If the non-stop words of the current time period do not coincide with the non-stop words of any one of the prior time periods (NO in Step 58), then the beginning of the current time period is marked as the start of a new commercial segment (Step 60). Thereafter, the method returns to Step 32.
If the non-stop words identified in the current time period coincide with the non-stop words of one of the prior time periods (YES in Step 58), then a notation is made that the current time period is part of the same commercial as the corresponding prior time period which has the same non-stop words (Step 62). Then a determination is made as to whether the current transcript information is indicative of a return of the non-commercial portion of the program (Step 50). If it is determined that the current transcript information corresponds to a return to the non-commercial portion of the program (YES n Step 50), the method returns to Step 24. However, if it is determined that the current transcript information is not indicative of a return to the non-commercial portion of the program (NO in Step 50), then the method returns to Step 32.
Returning now to Step 8, if it is determined that EPG data is not available (NO in Step 8), then the method continues with Step 63 shown in
Turning now to
If the non-stop words identified in the current time period and the non-stop words of the prior time period do not coincide (NO in Step 72), then the current and prior time periods are not part of the same commercial segment (Step 74) and the start of the current time period is marked as the start of a new commercial (Step 76). Thereafter, the transcript information is monitored for a next time period which overlaps with at least the prior time period and the non-stop words which occur more than a predetermined number of times above a threshold are noted (Step 78).
If in Step 78, non-stop words are identified in which occur more than a predetermined number of times (X>1 in Step 78), a determination is made as to whether the non-stop words of the current time period coincide with the non-stop words of prior time periods (Step 82). If the non-stop words of the current time period coincide with non-stop words of a prior time period (YES in Step 82), then a notation is made that the current time period is part of the same commercial as the prior time period (Step 84). Thereafter, a determination is made as to whether the current transcript information corresponds to a return to the non-commercial portion of the program (Step 86). If it is determined that the current transcript information corresponds to a return to the non-commercial portion of the program (YES in Step 86), the method returns to Step 63. However, if it is determined that the current transcript information is not indicative of a return to the non-commercial portion of the program (NO in Step 86), then the method returns to Step 68 to monitor the transcript information for a new time period.
If in Step 72, it is determined that the nonstop words of the current time period coincide with non-stop words of a prior time period (YES in Step 72), then it is determined that the prior time period and the current time period are part of the same commercial segment (Step 88). Thereafter, the transcript information is monitored for a next time period which preferably overlaps with at least the prior time period and the non-stop words which occur more than a predetermined number of times are noted (Step 90). If non-stop words occur more than a predetermined number of times in the current time period (X>1 in Step 90), a determination is made as to whether the non-stop words of the current time period coincide with the nonstop words of the prior time periods (Step 94). If the non-stop words of the current time period do not coincide with the non-stop words of any one of the prior time periods (NO in Step 94), then the start of the current time period is marked as the start of a new commercial (Step 98). Thereafter, the method returns to Step 68. If the non-stop words identified in the current time period coincide with the non-stop words of the prior time periods (YES in Step 94), then a notation is made that the current time period is part of the same commercial as the prior time period which has the same non-stop words (Step 96). Then a determination is made as to whether the current transcript information is indicative of a return of the non-commercial portion of the program (Step 86). If it is determined that the current transcript information corresponds to a return to the non-commercial portion of the program (YES in Step 86), the method returns to Step 63. However, if it is determined that the current transcript information is not indicative of a return to the non-commercial portion of the program (NO in Step 50), then the method returns to Step 68).
Based upon the above analysis, if non-stop words occur multiple times in a given time segment, and the same words occur for example in the next two overlapping time segments, the method stores the transcript text from the beginning of the first time period to the end of the third time segment as a possible commercial. Further, if it so happens that certain words occur multiple times in the third time segment and continue to occur until the sixth time segment, then the method stores the transcript text from the beginning of third time segment to the end of sixth time segment as a next commercial. The next time similar keywords are observed, then a sub-segment matching method can be used (explained below) to match the current possible commercial to the two commercials that are stored. This will match the overlapping part of one text to the other possible commercial texts. Assuming that the current commercial is bounded by different commercials than the prior occurrence of the same commercial, the next time the commercial appears, only the center portion of both the segments match the current commercial. This enables extraneous portions of the commercial segments to be removed from the stored commercial and what is left is only the subject commercial. This might include only a part of the first time segment, the entire second time segment and a part of the third time segment as the actual commercial.
As a result of the present invention, individual commercials of a multi-commercial portion of a broadcast program can be identified using transcript information and can be separated from each other and individually stored in memory for a variety of uses such as identifying individual commercials during a program and searching for a particular type of commercial (auto) or a commercial for a particular product (Honda Accord).
Based on analysis of actual broadcast commercials, the inventors have determined that if a non-stop word occurs at least three times within a pre-determined time period (15 seconds), this is indicative of the occurrence of a commercial. The inventors have discovered that it is unlikely that a non-stop word would occur in a non-commercial portion of a program more than three times during any 15 second interval.
The following text is the closed-captioned text extracted from the Late-Night Show with David Letterman which includes two commercials.
The closed-captioning text demonstrates the effectiveness of the invention wherein the words “Nizoral”, “A-D”, “dandruff”, and “shampoo” appeared at least three times during the first commercial (15 second) segment between time stamps 1374847 and 1449023. Moreover, the words “lauder” and “pleasures” appeared more than three times in the second commercial between time stamps 1451597 and 1528947. This is based on the fact that advertisers want to deliver their message in a short period of time and therefore must frequently repeat the product name, company and other identifying features of the product to the audience to convey the desired message and information in a short period of time. By detecting the occurrence of these non-stop words in the transcript information in a predetermined time period, individual commercials can be detected and separated from each other.
After a commercial portion of a program has been identified, the individual commercials within the commercial portion of a broadcast are preferably separated from one another and stored in memory/database for retrieval at a later time, (e.g., so that a user could retrieve a car advertisement by searching the memory/database of commercials) within the memory/database which stores the individual commercials to present the user with commercials which match the user's requirements.
Turning now to
Initially, a search for a new commercial area is conducted (Step 120). The search for a commercial area may correspond to the methods shown in
If the non-stop words of the new commercial area do not correspond to non-stop words of the commercials contained in the list of found commercials (NO in Step 126), then a comparison is made between the non-stop words of the new commercial area and the non-stop words of the commercials of the candidate list of commercials (Step 130). If the non-stop words of the new commercial area match the nonstop words of at least one of the commercials identified in the candidate list (YES in Step 132), then the commercial which was identified in the candidate list is deleted from the candidate's list and moved to the found commercial list along with the corresponding non-stop words and transcript text (Step 134). If, however, the non-stop words of the new commercial area do not match the non-stop words of the commercials contained in the candidate list (NO in Step 132), then a comparison is made between the non-stop words of the new commercial area and the non-stop words contained in the probable list of commercials (Step 136). If a match is found between the non-stop words of the new commercial area and the non-stop words of one of the commercials contained in the probable list of commercials (YES in Step 138), then the commercial identified from the list of probable commercials is deleted from the probable list of commercials and moved to the candidate list of commercials (Step 140). If, however, a match between non-stop words of the new commercial area and the non-stop words of one of the commercials contained in the list of probable commercials is not obtained, then the new commercial area which includes the identified non-stop words and the transcript text are stored in the probable list of commercials (Step 142).
In view of the method shown in
It is important to note that the above learning procedure is run continuously for programs that do not contain “going into commercial clues”.
The present invention is designed to store the transcripts and optionally a signature along with the commercial in a database. The system may also be coupled to a service provider which downloads or provides access to all of the currently airing commercials, or a memory/database of current commercials could be coupled to the system to provide commercial knowledge at initial start-up of the system. When the user wants to retrieve a specific type of advertisement (e.g., a car advertisement), the user can provide search parameters and a simple string matching will retrieve the desired commercial, searching the found list, candidate list and probable list in order. In addition, the transcripts of the stored commercials can be used as signatures to identify the advertisement during a broadcast program at a later time. The signature can also be used by advertisers to ensure that their commercials have been aired.
It should also be mentioned that the time periods for monitoring non-stop words can be any desired length. Since commercials are typically only 15 to 30 seconds long, it has been found that the time period should be preferably about 15 seconds in duration. While it is foreseen that the time periods need not overlap, it has been determined that overlapping time periods is preferable. In one example the first time period covers the time from zero seconds to 15 seconds, the second time period covers a time period from 5 seconds to 20 seconds, a third time period covers the period from 10 seconds to 25 seconds and the fourth time period covers a time from 15 seconds to 30 seconds. With this time period structure a more definitive indication of a beginning or end of commercial segments can be provided. If it is determined that the first, second and third time periods have the same non-stop words, then the transcript information for the first, second and third time periods are presented for storage together in the database.
It should be noted that the total number of time periods which can be linked together should be set to a limit (of about the equivalent of one or two minutes) so that an entire program is not stored due to the repetition of certain words or names. For example, since commercials are rarely over a minute long, no more than 12 overlapping 15 second windows as described above should be grouped together as a possible commercial.
It should also be noted that it is foreseen that the present invention could provide the user with links related to commercials that are viewed that the user might be interested in visiting. For example, if a user is viewing a particular car commercial, the user can be presented with loan commercials, car insurance commercials and/or car dealerships whose commercials are stored in the database.
It is also foreseen that the apparatus can include a database of commercials and brand names. If a specific brand name as identified by the database is mentioned numerous times within a predetermined period of time, this is indicative of the occurrence of a commercial. The database of commercials and commercial names can also aid in labeling a commercial as being for a particular product, and to identify how many commercials there are in a given commercial segment.
It is also foreseen that commercial segments of a program can be identified by observing the length (i.e., number of words) of each line of closed-captioned text. The system could determine a running average of words/line. If the number of words in a specific number of lines exceeds the running average, or if the closed-captioned format changes, this is indicative of a commercial segment.
Having described specific embodiments of the invention with reference to the accompanying drawing, it will be appreciated that the present invention is not limited to those precise embodiments and that various changes and modifications can be effected therein by one of ordinary skill in the art without departing from the scope or spirit of the invention defined by the appended claims.
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