Abstract: Systems and methods for audio listening devices, comprise a speaker coupled to a first housing, a sound port having a first end and a second end, wherein the first end is coupled to the first housing, and the second end is configured to be inserted in an ear canal of a person such that sound waves emitted from the speaker propagates via a secondary path to the ear canal through the sound port, active noise cancellation (ANC) components configured to generate anti-noise signals through the micro-speakers to cancel external noise, and a first microphone disposed within the sound port at the second end of the sound port such that the first microphone is configured to detect the anti-noise signal that propagates through the sound port via the secondary path and the external noise that propagates via a primary path.

Abstract: Systems and methods for enhancing a headset user's own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

Abstract: Systems and methods provide input and output mode control for audio processing on a user device. Audio processing may be configured by monitoring audio activity on a device having at least one microphone and a digital audio processing unit, collecting information from the monitoring of the activity, including an identification of at least one application utilizing audio processing, and determining a context for the audio processing, the context including at least one of a hardware, software, audio signal and/or environmental context. An audio signal processing configuration is determined based on the application and determined context, an associated audio signal processing mode is selected, and an optimized audio signal generated.

Abstract: Systems and methods for audio listening devices, comprise a speaker coupled to a first housing, a sound port having a first end and a second end, wherein the first end is coupled to the first housing, and the second end is configured to be inserted in an ear canal of a person such that sound waves emitted from the speaker propagates via a secondary path to the ear canal through the sound port, active noise cancellation (ANC) components configured to generate anti-noise signals through the micro-speakers to cancel external noise, and a first microphone disposed within the sound port at the second end of the sound port such that the first microphone is configured to detect the anti-noise signal that propagates through the sound port via the secondary path and the external noise that propagates via a primary path.

Abstract: Adaptive noise cancellation systems and methods comprise a reference sensor operable to sense environmental noise and generate a corresponding reference signal, an error sensor operable to sense noise in a noise cancellation zone and generate a corresponding error signal, a noise cancellation filter operable to receive the reference signal and generate an anti-noise signal to cancel the environmental noise in the cancellation zone, an adaptation module operable to receive the reference signal and the error signal and adaptively adjust the anti-noise signal.

Abstract: Systems and methods for enhancing a headset user’s own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

Abstract: Systems and methods for audio listening devices, comprise a speaker coupled to a first housing, a sound port having a first end and a second end, wherein the first end is coupled to the first housing, and the second end is configured to be inserted in an ear canal of a person such that sound waves emitted from the speaker propagates via a secondary path to the ear canal through the sound port, active noise cancellation (ANC) components configured to generate anti-noise signals through the micro-speakers to cancel external noise, and a first microphone disposed within the sound port at the second end of the sound port such that the first microphone is configured to detect the anti-noise signal that propagates through the sound port via the secondary path and the external noise that propagates via a primary path.

Abstract: Systems and methods for enhancing a headset user's own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

Abstract: Active noise cancellation systems and methods include a feedforward path configured to receive a reference signal comprising ambient noise and adaptively generate an anti-noise signal to cancel the ambient noise and comprising an adaptive gain component configured to adaptively adjust a gain of the anti-noise signal, and a logic device configured to determine a leakage profile based on the adaptive gain component. The feedforward path includes a feedforward adaptive filter tuned to generate the anti-noise signal corresponding to the reference signal in accordance with the determined leakage profile. The leakage profile is selected from a plurality of stored leakage profiles that are tuned for a corresponding gain, and which corresponds to an ear coupling condition associated with a fit between the active noise cancellation system and a user. An adaptive transparency filter receives the reference signal and generates an ambient inclusion signal for output to a user.

Abstract: Systems and methods for processing an audio signal include an audio input operable to receive an input signal comprising a time-domain, single-channel audio signal, a subband analysis block operable to transform the input signal to a frequency domain input signal comprising a plurality of k-spaced under-sampled subband signals, a reverberation reduction block operable to reduce reverberation effect, including late reverberation, in the plurality of k-spaced under-sampled subband signals, a noise reduction block operable to reduce background noise from the plurality of k-spaced under-sampled subband signals, and a subband synthesis block operable to transform the subband signals to the time-domain, thereby producing an enhanced output signal.

Abstract: Systems and methods for enhancing a headset user's own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

Abstract: Adaptive noise cancellation systems and methods comprise a reference sensor operable to sense environmental noise and generate a corresponding reference signal, an error sensor operable to sense noise in a noise cancellation zone and generate a corresponding error signal, a noise cancellation filter operable to receive the reference signal and generate an anti-noise signal to cancel the environmental noise in the cancellation zone, an adaptation module operable to receive the reference signal and the error signal and adaptively adjust the anti-noise signal.

Abstract: Active noise cancellation systems and methods include a feedforward path configured to receive a reference signal comprising ambient noise and adaptively generate an anti-noise signal to cancel the ambient noise and comprising an adaptive gain component configured to adaptively adjust a gain of the anti-noise signal, and a logic device configured to determine a leakage profile based on the adaptive gain component. The feedforward path includes a feedforward adaptive filter tuned to generate the anti-noise signal corresponding to the reference signal in accordance with the determined leakage profile. The leakage profile is selected from a plurality of stored leakage profiles that are tuned for a corresponding gain, and which corresponds to an ear coupling condition associated with a fit between the active noise cancellation system and a user. An adaptive transparency filter receives the reference signal and generates an ambient inclusion signal for output to a user.

Abstract: Adaptive noise cancellation systems and methods comprise a reference sensor operable to sense environmental noise and generate a corresponding reference signal, an error sensor operable to sense noise in a noise cancellation zone and generate a corresponding error signal, a noise cancellation filter operable to receive the reference signal and generate an anti-noise signal to cancel the environmental noise in the cancellation zone, an adaptation module operable to receive the reference signal and the error signal and adaptively adjust the anti-noise signal. The adaptation module includes a noise amplification control module operable to adaptively control noise amplification in at least one hiss region of the anti-noise signal, while achieving cancellation in non-hiss regions of the anti-noise signal.

Abstract: An end detector configured to receive the feature data and detect an end point of a keyword, and a start detector configured to receive an indication of the detected end point and process the feature data associated with corresponding input frames to detect a start point of the keyword. The start detector and end detector comprise neural networks trained through a process using a cross-entropy cost function for non-Region of Target (ROT) frames and a One-Spike Connectionist Temporal Classification cost function for ROT frames.

Abstract: A classification training system for binary and multi-class classification comprises a neural network operable to perform classification of input data, a training dataset including pre-segmented, labeled training samples, and a classification training module operable to train the neural network using the training dataset. The classification training module includes a forward pass processing module, and a backward pass processing module. The backward pass processing module is operable to determine whether a current frame is in a region of target (ROT), determine ROT information such as beginning and length of the ROT and update weights and biases using a cross-entropy cost function and One Spike Connectionist Temporal Classification (OSCTC) cost function. The backward pass module further computes a soft target value using ROT information and computes a signal output error using the soft target value and network output value.

Abstract: An acoustic event detection and classification system includes a start-end point detector and multi-class acoustic event classification. A classification training system comprises a neural network configured to perform classification of input data, a training dataset including pre-segmented, labeled training samples, and a classification training module configured to train the neural network using the training dataset. The classification training module includes a forward pass processing module, and a backward pass processing module. The backward pass processing module is configured to determine whether a current frame is in a region of target (ROT), determine ROT information such as beginning and length of the ROT and update weights and biases using a cross-entropy cost function and a many-or-one detection (MOOD) cost function. The backward pass module further computes a soft target value using ROT information and computes a signal output error using the soft target value and network output value.

Abstract: Adaptive noise cancellation systems and methods comprise a reference sensor operable to sense environmental noise and generate a corresponding reference signal, an error sensor operable to sense noise in a noise cancellation zone and generate a corresponding error signal, a noise cancellation filter operable to receive the reference signal and generate an anti-noise signal to cancel the environmental noise in the cancellation zone, an adaptation module operable to receive the reference signal and the error signal and adaptively adjust the anti-noise signal, and a transient activity detection module operable to receive the reference signal, detect a transient noise event and selectively disable the adaptation module during the detected transient noise event.

Abstract: Adaptive noise cancellation systems and methods include a reference sensor to sense environmental noise and generate a corresponding reference signal, an error sensor to sense noise in a noise cancellation zone and generate a corresponding error signal, a noise cancellation path including a noise cancellation filter and a variable gain component, the noise cancellation path receiving the reference signal and generating an anti-noise signal to cancel noise at an eardrum reference point, and an adaptation module to receive the reference signal and the error signal and adaptively adjust weights of the noise cancellation filter and/or the variable gain component. An adaptive gain control block updates the variable gain component. Inputs to the adaptive gain control block are conditioned using programmable filters to protect against low frequency transients and/or high frequency distractors in the environmental noise. The programmable filters are tuned to optimize cancellation at an eardrum reference point.

Abstract: An active noise cancellation system includes a sensor operable to sense environmental noise and generate a corresponding reference signal, a fixed noise cancellation filter including a predetermined model of the active noise cancellation system operable to generate an anti-noise signal, and a tunable noise cancellation filter operable to modify the anti-noise signal in accordance with stored coefficients, wherein the tunable noise cancellation filter is further operable to modify the stored coefficients in real-time based on user feedback and generate a tuned anti-noise signal that models tunable deviations from the predetermined noise model. A graphical user interface is operable to receive user adjustments of tunable parameters in real-time, the tunable parameters corresponding to at least one of the stored coefficients.