Abstract:
The disclosed system and method for a mobile device combines information derived from onboard sensors with conventional signal processing information derived from a speech or audio signal to assist in noise and echo cancellation. In some implementations, an Angle and Distance Processing (ADP) module is employed on a mobile device and configured to provide runtime angle and distance information to an adaptive beamformer for canceling noise signals, provides a means for building a table of filter coefficients for adaptive filters used in echo cancellation, provides faster and more accurate Automatic Gain Control (AGC), provides delay information for a classifier in a Voice Activity Detector (VAD), provides a means for automatic switching between a speakerphone and handset mode of the mobile device, or primary microphone and reference microphones and assists in separating echo path changes from double talk.
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:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.
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 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.
Abstract:
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.