Abstract: A method of providing custom audio processing in an audio device having an embedded audio DSP framework is disclosed. The audio device has an associated application that runs on a personal computing device. The method comprises receiving a notification of the availability of an audio processing configuration file, the audio processing configuration file identifying audio modules, interconnections between the audio modules and related settings for custom audio processing, transmitting a request for the audio processing configuration file from the personal computing device, receiving the audio processing configuration file at the personal computing device, transmitting the audio processing configuration file to the audio device from the personal computing device, and loading the audio processing configuration file into the audio device.

Abstract: An apparatus and method for auto echo cancellation utilizing an occluded voice sensor. The technology as disclosed and claimed herein and the various implementations and embodiments improves Acoustic Echo Cancellation (AEC) system performance by increasing cancellation quality and speech SNR by the replacement of the lower frequency portion of the microphone signal with the signal of an Occluded Voice Sensor (OVS) signal and never including the spectral band in the transmission. This frequency band replacement excludes the reinjection of that band from the speaker.

Abstract: A system and method for improving the performance of a hands-free voice user interface system while minimizing the computational complexity without sacrificing performance. Specifically, when estimating the location of the talker for the purpose of steering a directional beam in the direction of the active talker. A hands-free voice user interface system requires a clean signal to be streamed to the cloud for recognition. One way to improve the speech signal is to estimate where the talker is and steer a beam in the direction of the active talker. To locate the talker to a localized position, a direction of arrival estimator (DOA) algorithm is used. DoA generally requires noise and echo free signal for optimal estimation, but it is computationally expensive to run audio pre-processing such as an acoustic echo cancellation for each microphone in microphone array.

Abstract: Generating an audio processing design includes placing representations of audio processing modules using a user interface. The method includes causing the display of the representations of the audio processing modules in the user interface, receiving user input to place a representation of a start thread module in the audio processing design between a representation of an upstream audio module and representations of downstream audio modules, the representation of the start thread module having data associated therewith that defines a buffer up factor and a thread identifier, receiving user input to specify the buffer up factor and thread identifier associated with the representation of the start thread module, and applying the specified thread identifier and a sample block size that is derived from the specified buffer up factor, downstream from the representation of the thread start module.

Abstract: A method and apparatus for handling both echo cancellation and noise in a given space using a single adaptive filter. The proposed method utilizes just a single adaptive filter and without any control logic, the system is capable of handling both the AEC and the noise in a given space. The technology as proposed and claimed herein proposes using a single adaptive filter to cancel referenced noise AEC and unreferenced noise ANC in a given physical space using a beamformer. By adding the far end reference and a beam pointed dynamically on the noise source in the given physical space this can be achieved. This invention also reduces the processing load and memory.

Abstract: A system and method for improving the performance of a hands-free voice user interface system while minimizing the computational complexity without sacrificing performance. Specifically, when estimating the location of the talker for the purpose of steering a directional beam in the direction of the active talker. A hands-free voice user interface system requires a clean signal to be streamed to the cloud for recognition. One way to improve the speech signal is to estimate where the talker is and steer a beam in the direction of the active talker. To locate the talker to a localized position, a direction of arrival estimator (DOA) algorithm is used. DoA generally requires noise and echo free signal for optimal estimation, but it is computationally expensive to run audio pre-processing such as an acoustic echo cancellation for each microphone in microphone array.