Other

Zhone Technologies, Inc.

Noise Free Wireless, Inc.

Alberto D Berstein

Alon Konchitsky

Sandeep Kulakcherla

William Martin Ribble

Kevin R Fitzgerald

Don Seferovich

Wen Wang

Israel Yuval

Tom Wei

Abraham Wei

Hariharan Ganapathy Kathirvelu

Mendy Segal

Embodiments of the invention provide a communication device and methods for enhancing audio signals. A first audio signal buffer and a second audio signal buffer are acquired. Thereafter, the second audio signal is processed based on the linear predictive coding coefficients and gains based on noise power of the first audio signal to generate an enhanced second audio signal.

Handset intelligibility enhancement system using adaptive filters and signal buffers

Embodiments of the invention provide a communication device and methods for enhancing audio signals. A first audio signal buffer and a second audio signal buffer are acquired. Thereafter, the magnitude spectrum calculated from the Fast Fourier Transform (FFT) of the second audio signal is processed based on the Linear Predictive Coding (LPC) spectrum of the first audio signal to generate an enhanced second audio signal.

Receiver intelligibility enhancement system

The present invention provides a novel system and method for monitoring the audio signals, analyze selected audio signal components, compare the results of analysis with a threshold value, and enable or disable noise reduction capability of a communication device.

Machine for enabling and disabling noise reduction (MEDNR) based on a threshold

A special purpose machine measures and modulates communication signals that are parsed into frames. Frames of signals modulated and measured to have certain qualities are deemed to be the result of wind noise. Frames of wind noise are cancelled from further use within a communication system.

Wind noise classifier

A noisy signal is picked up by a microphone, digitized by an Analog to Digital Converter and fed to a processor for analysis and wind noise reduction. Most of noise reduction methods are based on the assumption that the interfering noise is stationary or slowly varying compared with speech. This assumption allows 'learning' the characteristics of the noise between speech pauses and, based on a noise estimate, to build different filters that reduce the noise. In the case of wind noise this basic assumption is not valid. Wind noise is highly non-stationary, its power and spectral characteristics vary greatly. Because wind noise is not stationary, regular noise reduction methods cannot be used to reduce wind noise. For reducing wind noise effects in a device, the presence of wind should be detected reliably and then a novel approach presented here must be applied to eliminate the wind noise.

Method for wind noise reduction

Embodiments of the invention provide a communication device and methods for generating enhanced audio signals. An audio signal comprising a speech signal and a noise signals is acquired at the communication device. A noise processor of the communication device detects a pitch estimation of the audio signal. Thereafter, the audio signal is processed based on the pitch estimation and processing parameters of the audio signals to remove noise signals and generate an enhanced audio signal.

System and method for biometric acoustic noise reduction

The present invention relates to means and methods of classifying speech and music signals in voice communication systems, devices, telephones, and methods, and more specifically, to systems, devices, and methods that automate control when either speech or music is detected over communication links. The present invention provides a novel system and method for monitoring the audio signal, analyze selected audio signal components, compare the results of analysis with a pre-determined threshold value, and classify the audio signal either as speech or music.

Speech and music discriminator for multi-media application

A clear, high quality voice signal with a high signal-to-noise ratio is achieved by use of an adaptive noise reduction scheme with two microphones in close proximity. The method includes the use of two omini directional microphones in a highly directional mode, and then applying an adaptive noise cancellation algorithm to reduce the noise.

Dual adaptive structure for speech enhancement

In assessing the capability of an IP based network to support toll telephony service, objective measurements of Speech Quality are taken. A module is used with Voice over Packet equipment that allows performance of voice quality measurements in real-time without using any external test equipment. A reference signal that includes a marker and a voice test signal is sent through the network from one Voice over Packet equipment containing or connected to the module to another. The received marker is compared to the reference marker to identify the onset time of the received voice test signal. The received and reference voice test signals are processed to measure the quality of the network. This may be implemented using the processing power and memory resources present in Voice over Packet equipment giving the network administrator an enhanced test capability at each node of the network. Voice quality measurements may be generated in a transparent way for the callers in real-time under severely degraded conditions of the network.

System for real time voice quality measurement in voice over packet network

A system and method of Acoustic Echo Cancellation includes a digital filter used to estimate the echo path is split into 2 filters: one fixed infinite impulse response (IIR) filter and one adaptive finite impulse response (FIR) filter. The fixed filter models the composite frequency response of the loudspeaker, its cabinet enclosure and the direct coupling path between the loudspeaker and the microphone(s). The adaptive filter models the time varying characteristics of the indirect coupling path between the loudspeaker and microphone.

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Cupertino, CA, United States of America

Alberto D Berstein