Audio control systems strive to produce distortion-free and/or accurate audio reproductions. The physical placement of loudspeakers relative to listeners impacts the ability of the audio control system to meet these goals. Standards such as those defined by the International Telecommunications Union (ITU), Dolby Laboratories, THX LTD, and others guide the placement of loudspeakers relative to listeners to achieve good results.
Due to environmental constraints, such as room size, furniture placement, and/or listener preferences, the physical placement of loudspeakers may not comply with the ITU, Dolby Laboratories, THX LTD, or other standards. Lack of compliance with a standard may lead to an inferior listener experience.
Non-limiting and non-exhaustive examples of the disclosure are described in conjunction with the figures described below.
Audio control systems can be configured to produce distortion-free and/or accurate audio reproductions. The physical placement of loudspeakers relative to listeners impacts the ability of the audio control system to meet these goals. Standards such as those defined by the International Telecommunications Union (ITU), Dolby Laboratories, THX LTD, and others guide the placement of loudspeakers relative to listeners to achieve good results.
Due to constraints in an environment such as room size, furniture placement, and/or listener preferences, the physical placement of loudspeakers may not comply with an established standard. Lack of compliance with standards may lead to an inferior listener experience. According to the systems and methods described herein, audio control systems may adjust drive outputs connected to loudspeakers to modify the generated soundfield to mimic or simulate a standards-based physical loudspeaker placement. The soundfield may cause a listener to perceive the speakers in a standard layout, which may improve listener experience and/or facilitate a more accurate reproduction of an intended audio composition.
As described herein, an audio control system may include an imaging sensor to capture an image of an environment containing loudspeakers connected to the audio control system. A listening position subsystem may process the captured image to identify a listening position within the environment. A speaker position subsystem may process the captured image to determine a physical location of each loudspeaker relative to the identified user listening position. A signal processing subsystem may modify an output signal driving the loudspeakers to steer a soundfield generated by the loudspeakers.
As an example, the audio control system may modify at least one of a directivity response, an on-axis frequency response, a frequency response, and a sound pressure level (SPL) parameter of any number of loudspeakers to attain a target soundfield that maps a perceived location of loudspeakers to the target layout. As a further example, modifying the drive outputs of the audio control system may include digital filtering and digital equalization prior to digital-to-analog conversion of the drive outputs used to drive the loudspeakers.
The audio control system may include a processor, memory, and/or hardware components to implement the various subsystems such that, at the identified user listening position, a perceived location of one of the loudspeakers is mapped to a location that is different than its physical location. In some examples, the audio control system may utilize computer-vision to identify objects in the environment, including couches, chairs, loudspeakers, and/or listeners. A distance measurement subsystem may measure a distance from each loudspeaker to the user listening position and/or between loudspeakers.
Some implementations may determine distances based on image analysis alone. Other implementations may utilize an ultrasonic distance measurement device and/or an optical time-of-flight measurement device. Still other implementations may utilize a microphone to measure test-tone delays. Image analysis may provide additional information, such as listener location, object detection, etc. that may not be available using test-tone or audio-only measurement approaches.
Standards bodies such as the International Telecommunications Union (ITU), Dolby Laboratories, THX LTD, and others recommend loudspeaker and listener layouts. Examples of recommended layouts include ITU-R BS.2159, Real 5.1, DTS, THX, ITU-R BS 775-1, and others.
In some examples, imaging systems may acquire still images, sequences of still images, and/or video. In some examples, imaging systems may acquire two-dimensional images, three-dimensional images, and/or images of higher dimensionality. In some examples, images may be acquired using visible and/or non-visible electromagnetic radiation.
In some examples, an audio control system 206 may receive manually acquired information (e.g., via a user-acquired image and/or user-defined layout) identifying the position and/or orientation of loudspeakers 202, 204, 208, 210, 214, and 220 and/or other objects within an environment (e.g., couches, chairs, tables, windows, walls, etc.). In some examples, the audio control system 206 may acquire position and/or orientation information of loudspeakers by evaluating a generated soundfield. In some examples, the audio control system 206 may determine object location using echolocation. In some examples, an audio control system 206 may facilitate the collection of position and/or orientation information through another mechanism, such as via Bluetooth, WIFI, and/or GPS systems.
In some examples, the audio control system may utilize the illustrated, or another, deep learning model to identify objects. In some examples, other object detection and/or identification approaches may be used. Examples of other approaches include genetic evolution network models, neural network models, machine learning models, other artificial intelligence models, deterministic models, and/or other approaches. The illustrated deep learning model includes various convolutional and dense block layers. In various examples, a deep learning model may utilize a layer-pooling convolutional neural network approach for object detection and identification.
In some examples, collected images may be used to determine the objects within the environment. For example, the processed images may identify the location and/or orientation of loudspeakers 404, 406, 408, 412, and 414 and/or listener position 402. In some examples, this information may be used to create a representation of the physical location of loudspeakers and listener positions and/or their positions relative to one another. In some examples, the positions of objects of interest relative to one another may be measured in two-dimensional space. In other examples, the dimensionality of the space of interest may be higher. For example, the audio control system may determine the relative positions of objects of interest in three-dimensional space. In various examples, the audio control system may determine locations relative to the listening position, a television or other video display, and/or an audio control system, such as an audio video receiver (AVR), an amplifier, an equalizer, or other audio processing and/or driving equipment.
In the illustrated example, the audio control system utilizes a deep learning model to identify the location and orientation of loudspeakers Front L 404, Front R 408, Center 406, Surround L 412, and Surround R 414. In addition, the deep learning model identifies a listener position 402. In this example, due to environmental constraints and/or listener preference, the relative position of the listener position 402 and loudspeakers 404, 408, 406, 412, and 414 do not comply with a standard layout.
In some examples, the acoustic control system may further process acquired images (e.g., using a deep learning model) to determine the position and/or orientation of loudspeakers 508 relative to a listener position. In some examples, the position and/or orientation of loudspeakers relative to a listener position are compared to a standard loudspeaker layout 510. The acoustic control system may consider the standard loudspeaker layout a “target” or “goal” layout for the loudspeakers. The audio control system may adjust or filter the drive outputs 512 to modify the generated soundfield to mimic a standard loudspeaker layout. That is, the audio control system may modify the drive outputs 512 so that a listener in the determined user listening position (at 506) will perceive the loudspeakers as if they were laid out according to the standard loudspeaker layout.
In some examples, a listener, acoustic engineer, setup technician, or another user may manually input the acoustic properties of loudspeakers into an audio control system. Alternatively or additionally, a user may manually provide enclosure sizes, enclosure types, driver sizes, brand names, and/or models of loudspeakers into audio control systems. In some examples, the audio control system may utilize a deep learning model to evaluate images containing loudspeakers of interest to determine the enclosure sizes, enclosure types, driver sizes, brand names, and/or models.
Specific examples and applications of the disclosure are described above and illustrated in the figures. It is, however, understood that many adaptations and modifications could be made to the precise configurations and components detailed above. In some cases, well-known features, structures, or operations are not shown or described in detail. Furthermore, the described features, structures, or operations may be combined in any suitable manner. It is also appreciated that the components of the examples as generally described and illustrated in the figures herein could be arranged and designed in a wide variety of different configurations. Thus, all feasible permutations and combinations of examples are contemplated.
In the description above, various features are sometimes grouped together in a single example, figure, or description thereof for the purpose of streamlining the disclosure. This method of disclosure, however, is not to be interpreted as reflecting an intention that any claim requires more features than those expressly recited in that claim. Rather, as the following claims reflect, inventive aspects lie in a combination of fewer than all features of any single foregoing disclosed example. Thus, the claims are hereby expressly incorporated into this Detailed Description, with each claim standing on its own as a separate example. This disclosure includes all permutations and combinations of the independent claims with their dependent claims.
Filing Document | Filing Date | Country | Kind |
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PCT/US2019/038598 | 6/21/2019 | WO | 00 |