Starkey Laboratories, Inc.

Apple Inc.

Lalin S Theverapperuma

Vasu Iyengar

Sean Anthony Ramprashad

Jon Schmidt Kindred

Harikrishna P Natarajan

Arthur Salvetti

Johnson O Sebeni

Jianxiong Shi

Sree Ram Kodali

Madhusudan Chaudhary

Navid Damji

Samy Khay-Ibbat

Thanigaivelu Elangovan

Esge Brandt Andersen

Sorin V Dusan

Joshua D Atkins

Srinivasan Vasudevan

Giri Prassad Deivasigamani

Baptiste Pierre Paquier

Luciano Miguel Verger

Onur E Tackin

Shivesh Makharia

Tarun Pruthi

Muhammad Adeel Alam

Sarmad Aziz Malik

Raghavendra S Prabhu

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.

Coordination of beamformers for noise estimation and noise suppression

Method of speech enhancement using Neural Network-based combined signal starts with training neural network offline which includes: (i) exciting at least one accelerometer and at least one microphone using training accelerometer signal and training acoustic signal, respectively. The training accelerometer signal and the training acoustic signal are correlated during clean speech segments. Training neural network offline further includes (ii) selecting speech included in the training accelerometer signal and in the training acoustic signal, and (iii) spatially localizing the speech by setting a weight parameter in the neural network based on the selected speech included in the training accelerometer signal and in the training acoustic signal. The neural network that is trained offline is then used to generate a speech reference signal based on an accelerometer signal from the at least one accelerometer and an acoustic signal received from the at least one microphone. Other embodiments are described.

System and method for performing speech enhancement using a neural network-based combined symbol

A station that generates data packets to be transmitted by the station such that the data packets spend a minimum amount of time in a buffer prior to transmission. The method includes receiving a specification for a connected discontinuous reception (C-DRX) cycle, the specification indicating when a plurality of onDurations of the C-DRX cycle occurs, the onDurations having a predetermined interval therebetween, receiving data at a known time relative to the C-DRX cycle, determining a modification to a conversion process that converts the data to data packets such that the data packets are stored in a buffer at a subframe immediately preceding one of the onDurations subsequent to the known time, performing the conversion process based upon the modification and storing the data packets at the subframe immediately preceding the one of the onDurations. In one embodiment, the data is raw audio data and the data packets are audio packets.

System and method for audio frame generation alignment with LTE transmission opportunities

A headset that communicates with a mobile device through a local radio frequency (RF) communication link to conduct a telephone call is described. The headset includes a local RF communication modem that receives downlink packets from the mobile device through the local RF communication link. The downlink packets were received by the mobile device through a wireless communication link. The headset includes an audio decoder that decodes the downlink packets into a downlink audio signal to be played back at the headset. The headset also includes an audio encoder that encodes an uplink audio signal produced by the headset into uplink packets. The local RF communication modem sends the uplink packets to the mobile device through the local RF communication link. Other embodiments are also described and claimed.

Cellular network communications wireless headset and mobile device

System of improving sound quality includes loudspeaker, microphone, accelerometer, acoustic-echo-cancellers (AEC), and double-talk detector (DTD). Loudspeaker outputs loudspeaker signal including downlink audio signal from far-end speaker. Microphone generates microphone uplink signal and receives at least one of: near-end speaker, ambient noise, and loudspeaker signals. Accelerometer generates accelerometer-uplink signal and receives at least one of: near-end speaker, ambient noise, and loudspeaker signals. First AEC receives downlink audio, microphone-uplink and double talk control signals, and generates AEC-microphone linear echo estimate and corrected AEC-microphone uplink signal. Second AEC receives downlink audio, accelerometer uplink and double talk control signals, and generates AEC-accelerometer linear echo estimate and corrected AEC-accelerometer uplink signal. DTD receives downlink audio signal, uplink signals, corrected uplink signals, linear echo estimates, and generates double-talk control signal. Uplink audio signal including at least one of corrected microphone-uplink signal and corrected accelerometer-uplink signal is generated. Other embodiments are described.

System and method of double talk detection with acoustic echo and noise control

A method of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using an adaptive filter to measure an acoustic feedback path from the receiver to the microphone and adjusting an adaptation rate of the adaptive filter using an output from a filter having an autoregressive portion, the output derived at least in part from a ratio of a predictive estimate of the input signal to a difference of the predictive estimate and the input signal.

Entrainment avoidance with an auto regressive filter

A system of signal processing an input signal in a hearing assistance device to avoid entrainment wherein the hearing assistance device including a receiver and a microphone, the method comprising using an adaptive filter to estimate an acoustic feedback path from the receiver to the microphone, generating one or more estimated future pole positions of a transfer function of the adaptive filter, analyzing stability of the one or more estimated pole positions for an indication of entrainment and adjusting the adaptation of the adaptive filter based on the stability.

Entrainment avoidance with pole stabilization

A system of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using a transform domain adaptive filter including two or more eigenvalues to measure an acoustic feedback path from the receiver to the microphone, analyzing a measure of eigenvalue spread against a predetermined threshold for indication of entrainment of the transform domain adaptive feedback cancellation filter, and upon indication of entrainment of the transform domain adaptive feedback cancellation filter, modulating the adaptation of the transform domain adaptive feedback cancellation filter.

Entrainment avoidance with a transform domain algorithm

Method and apparatus for signal processing an input signal in a hearing assistance device to avoid entrainment, the hearing assistance device including a receiver and a microphone, the system comprising using a gradient adaptive lattice filter including one or more reflection coefficients to measure an acoustic feedback path from the receiver to the microphone of the hearing assistance device.

Entrainment avoidance with a gradient adaptive lattice filter

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Cupertino, CA, United States of America

Lalin S Theverapperuma