Abstract:
Systems and methods are described for storing and reusing previously generated/calculated acoustic environment data. By reusing acoustic environment data, the systems and methods described herein may avoid the increased overhead in generating/calculating acoustic environment data for a location when this data has already been generated and is likely accurate. In particular, the time and complexity involved in determining reverberation/echo levels, noise levels, and noise types may be avoided when this information is available in storage. This previously stored acoustic environment data may not be limited to data generated/calculated by the same audio device. Instead, in some embodiments an audio device may access a centralized repository to leverage acoustic environment data generated/calculated by other audio devices.
Abstract:
A method for adapting a threshold used in multi-channel audio voice activity detection. Strengths of primary and secondary sound pick up channels are computed. A separation, being a measure of difference between the strengths of the primary and secondary channels, is also computed. An analysis of the peaks in separation is performed, e.g. using a leaky peak capture function that captures a peak in the separation and then decays over time, or using a sliding window min-max detector. A threshold that is to be used in a voice activity detection (VAD) process is adjusted, in accordance with the analysis of the peaks. Other embodiments are also described and claimed.
Abstract:
Aspects of the subject technology provide for generation of a self-voice signal by an electronic device that is operating in an active noise cancellation mode. In this way, during a phone call, a video conference, or while listening to audio content, a user of the electronic device may benefit from active cancellation of ambient noise while still being able to hear their own voice when they speak. In various implementations described herein, the concurrent self-voice and automatic noise cancellation features are facilitated by accelerometer-based control of sidetone and/or active noise cancellation operations.
Abstract:
An audio system has an ambient sound enhancement function, in which an against-the-ear audio device having a speaker converts a digitally processed version of an input audio signal into sound. The audio system also has an acoustic noise cancellation (ANC) function that may be combined in various ways with the sound enhancement function, and that may be responsive to voice activity detection. Other aspects are also described and claimed.
Abstract:
System of noise reduction for mobile devices includes blind source separator (BSS) and noise suppressor. BSS receives signals from at least two audio pickup channels. BSS includes sound source separator, voice source detector, equalizer, and auto-disabler. Sound source separator generates signals representing first sound source and second sound source based on signals from the first and the second channels. Voice source detector determines whether the signals representing the first and second sound sources are voice signal or noise signal, respectively. Equalizer scales noise signal to match a level of the voice signal, and generates scaled noise signal. Auto-disabler determines whether to disable BSS. Auto-disabler outputs signals from the at least two audio pickup channels when the BSS is disabled and outputs the voice signal and the scaled noise signal when the BSS is not disabled. Noise suppressor generates clean signal based on outputs from auto-disabler. Other embodiments are also described.
Abstract:
System of noise reduction for mobile devices includes blind source separator (BSS) and noise suppressor. BSS receives signals from at least two audio pickup channels. BSS includes sound source separator, voice source detector, equalizer, and auto-disabler. Sound source separator generates signals representing first sound source and second sound source based on signals from the first and the second channels. Voice source detector determines whether the signals representing the first and second sound sources are voice signal or noise signal, respectively. Equalizer scales noise signal to match a level of the voice signal, and generates scaled noise signal. Auto-disabler determines whether to disable BSS. Auto-disabler outputs signals from the at least two audio pickup channels when the BSS is disabled and outputs the voice signal and the scaled noise signal when the BSS is not disabled. Noise suppressor generates clean signal based on outputs from auto-disabler. Other embodiments are also described.
Abstract:
Digital signal processing techniques for automatically reducing audible noise from a sound recording that contains speech. A noise suppression system uses two types of noise estimators, including a more aggressive one and less aggressive one. Decisions are made on how to select or combine their outputs into a usable noise estimate in a different speech and noise conditions. A 2-channel noise estimator is described. Other embodiments are also described and claimed.
Abstract:
An audio system has a housing in which are integrated a number of microphones. A programmed processor accesses the microphone signals and produces a number of acoustic pick up beams based groups of microphones, an estimation of voice activity and an estimation of noise characteristics on each beam. Two or more beams including a voice beam that is used to pick up a desired voice and a noise beam that is used to provide information to estimate ambient noise are adaptively selected from among the plurality of beams, based on thresholds for voice separation and thresholds for noise-matching. Other embodiments are also described and claimed.
Abstract:
A method for adapting a threshold used in multi-channel audio voice activity detection. Strengths of primary and secondary sound pick up channels are computed. A separation, being a measure of difference between the strengths of the primary and secondary channels, is also computed. An analysis of the peaks in separation is performed, e.g. using a leaky peak capture function that captures a peak in the separation and then decays over time, or using a sliding window min-max detector. A threshold that is to be used in a voice activity detection (VAD) process is adjusted, in accordance with the analysis of the peaks. Other embodiments are also described and claimed.
Abstract:
Digital signal processing for microphone partial occlusion detection is described. In one embodiment, an electronic system for audio noise processing and for noise reduction, using a plurality of microphones, includes a first noise estimator to process a first audio signal from a first one of the microphones, and generate a first noise estimate. The electronic system also includes a second noise estimator to process the first audio signal, and a second audio signal from a second one of the microphones, in parallel with the first noise estimator, and generate a second noise estimate. A microphone partial occlusion detector determines a low frequency band separation of the first and second audio signals and a high frequency band separation of the first and second audio signals to generate a microphone partial occlusion function that indicates whether one of the microphones is partially occluded.