Abstract:
A method for multi-channel echo cancellation and noise suppression is described. One of multiple echo estimates is selected for non-linear echo cancellation. Echo notch masking is performed on a noise-suppressed signal based on an echo direction of arrival (DOA) to produce an echo-suppressed signal. Non-linear echo cancellation is performed on the echo-suppressed signal based, at least in part, on the selected echo estimate.
Abstract:
A crosstalk cancelation technique reduces feedback in a shared acoustic space by canceling out some or all parts of sound signals that would otherwise be produced by a loudspeaker to only be captured by a microphone that, recursively, would cause these sounds signals to be reproduced again on the loudspeaker as feedback. Crosstalk cancelation can be used in a multichannel acoustic system (MAS) comprising an arrangement of microphones, loudspeakers, and a processor to together enhance conversational speech between in a shared acoustic space. To achieve crosstalk cancelation, a processor analyzes the inputs of each microphone, compares it to the output of far loudspeaker(s) relative to each such microphone, and cancels out any portion of a sound signal received by the microphone that matches signals that were just produced by the far loudspeaker(s) and sending only the remaining sound signal (if any) to such far loudspeakers.
Abstract:
A multi-channel sound (MCS) system features intelligent calibration (e.g., of acoustic echo cancelation (AEC)) for use in dynamic acoustic environments. A sensor subsystem is utilized to detect and identify changes in the acoustic environment and determine a “scene” corresponding to the resulting acoustic characteristics for that environment. This detected scene is compared to predetermined scenes corresponding to the acoustic environment. Each predetermined scene has a corresponding pre-tuned filter configuration for optimal AEC performance. Based on the results of the comparison, the pre-tuned filter configuration corresponding to the predetermined scene that most closely matches the detected scene is utilized by the AEC subsystem of the multi-channel sound system.
Abstract:
Adaptations for in-vehicle adaptive noise-canceling (ANC) technology are described. An example in-vehicle audio system includes ANC circuitry coupled to one or more error microphones. The ANC circuitry being configured to process audio data received from the one or more error microphones to determine a distinction between the engine-external noise and the engine noise. The ANC circuitry is further configured to alter, based on the distinction determined between the engine-external noise and the engine noise, a convergence between two or more ANC filters to form altered-convergence ANC filtering coefficients.
Abstract:
A multi-channel sound (MCS) system features intelligent calibration (e.g., of acoustic echo cancellation (AEC)) for use in dynamic acoustic environments. A sensor subsystem is utilized to detect and identify changes in the acoustic environment and determine a “scene” corresponding to the resulting acoustic characteristics for that environment. This detected scene is compared to predetermined scenes corresponding to the acoustic environment. Each predetermined scene has a corresponding pre-tuned filter configuration for optimal AEC performance. Based on the results of the comparison, the pre-tuned filter configuration corresponding to the predetermined scene that most closely matches the detected scene is utilized by the AEC subsystem of the multi-channel sound system.
Abstract:
A multichannel acoustic system (MAS) comprises an arrangement of microphones, loudspeakers, and filters along with a multichannel acoustic processor (MAP) and other components to together provide and enhance the auditory experience of persons in a shared acoustic space such as, for example, the driver and other passengers in an automobile. Driver-specific features such as navigation and auditory feedback cues are described, as individual auditory customizations and collective communications both within the shared acoustic space as well as with other individuals not located in the space via enhanced conference call facilities.
Abstract:
Apparatus and methods for audio noise attenuation are disclosed. An audio signal analyzer can determine whether an input audio signal received from a microphone device includes a noise signal having identifiable content. If there is a noise signal having identifiable content, a content source is accessed to obtain a copy of the noise signal. An audio canceller can generate a processed audio signal, having an attenuated noise signal, based on comparing the copy of the noise signal to the input audio signal. Additionally or alternatively, data may be communicated on a communication channel to a separate media device to receive at least a portion of the copy of the noise signal from the separate media device, or to receive content-identification data corresponding to the content source.
Abstract:
Apparatus and methods for audio noise attenuation are disclosed. An audio signal analyzer can determine whether an input audio signal received from a microphone device includes a noise signal having identifiable content. If there is a noise signal having identifiable content, a content source is accessed to obtain a copy of the noise signal. An audio canceller can generate a processed audio signal, having an attenuated noise signal, based on comparing the copy of the noise signal to the input audio signal. Additionally or alternatively, data may be communicated on a communication channel to a separate media device to receive at least a portion of the copy of the noise signal from the separate media device, or to receive content-identification data corresponding to the content source.