Hughes Electronics Corporation

Srinivas Nandkumar

Kumar Swaminathan

Gaguk Zakaria

Bangalore R Udaya Bhaskar

Filiz Basbug Ertem

A system determines a voicing measure as a measure of the degree of signal periodicity and uses the determined voicing measure to quantize the spectral magnitude of the slowly evolving waveform (SEW) and the modeling of the SEW and rapidly evolving waveform (REW) phase spectra.

Voicing measure as an estimate of signal periodicity for a frequency domain interpolative speech codec system

Encoding of prototype waveform components applicable to telecommunication systems provides improved voice quality enabling a dual-channel mode of operation which permits more users to communicate over the same physical channel. A prototype word (PW) gain is vector quantized using a vector quantizer (VQ) that explicitly populates a codebook by representative steady state and transient vectors of PW gain for tracking the abrupt variations in speech levels during onsets and other non-stationary events, while maintaining the accuracy of the speech level during stationary conditions.

Spectral magnitude modeling and quantization in a frequency domain interpolative speech codec system

An improved noise reduction algorithm is provided, as well as a voice activity detector, for use in a voice communication system. The voice activity detector allows for a reliable estimate of noise and enhancement of noise reduction. The noise reduction algorithm and voice activity detector can be implemented integrally in an encoder or applied independently to speech coding application. The voice activity detector employs line spectral frequencies and enhanced input speech which has undergone noise reduction to generate a voice activity flag. The noise reduction algorithm employs a smooth gain function determined from a smoothed noise spectral estimate and smoothed input noisy speech spectra. The gain function is smoothed both across frequency and time in an adaptive manner based on the estimate of the signal-to-noise ratio. The gain function is used for spectral amplitude enhancement to obtain a reduced noise speech signal. Smoothing employs critical frequency bands corresponding to the human auditory system. Swirl reduction is performed to improve overall human perception of decoded speech.

Method of noise reduction for speech codecs

Encoding of prototype waveform components applicable to GeoMobile and Telephony Earth Station (TES) providing improved voice quality enabling a dual-channel mode of operation which permits more users to communicate over the same physical channel. A prototype word (PW) gain is vector quantized using a vector quantizer (VQ) that explicitly populates the codebook by representative steady state and transient vectors of PW gain for tracking the abrupt variations in speech levels during onsets and other non-stationary events, while maintaining the accuracy of the speech level during stationary conditions. The rapidly evolving waveform (REW) and slowly evolving waveform (SEW) component vectors are converted to magnitude-phase. The variable dimension SEW magnitude vector is quantized using a hierarchical approach, i.e., a fixed dimension SEW mean vector computed by a sub-band averaging of SEW magnitude spectrum, and only the REW magnitude is explicitly encoded. The REW magnitude vector sequence is normalized to unity RMS value, resulting in a REW magnitude shape vector and a REW gain vector. The normalized REW magnitude vectors are modeled by a multi-band sub-band model which converts the variable dimension REW magnitude shape vectors, e.g., six dimensional REW sub-band vectors. The sub-band vectors are averaged over time, resulting in a single average REW sub-band vector for each frame. At the decoder, the full-dimension REW magnitude shape vector is obtained from the REW sub-band vector by a piecewise-constant construction. The REW phase vector is regenerated at the decoder based on the received REW gain vector and the voicing measure, which determines a weighted mixture of SEW component and a random noise that is passed through a high pass filter to generate the REW component. The high pass filter poles are adjusted based on the voicing measure to control the REW component characteristics. At the output the filter, the magnitude of the REW component is scaled to match the received REW magnitude vector.

Frequency domain interpolative speech codec system

A speech mode based multi-stage vector quantizer is disclosed which quantizes and encodes line spectral frequency (LSF) vectors that were obtained by transforming the short-term predictor filter coefficients in a speech codec that utilizes linear predictive techniques. The quantizer includes a mode classifier that classifies each speech frame of a speech signal as being associated with one of a voiced, spectrally stationary (Mode A) speech frame, a voiced, spectrally non-stationary (Mode B) speech frame and an unvoiced (Mode C) speech frame. A converter converts each speech frame of the speech signal into an LSF vector and an LSF vector quantizer includes a 12-bit, two-stage, backward predictive vector encoder that encodes the Mode A speech frames and a 22 bit, four-stage backward predictive vector encoder that encodes the Mode 13 and the Mode C speech frames.

Growing community of inventors

Rockville, MD, United States of America

Srinivas Nandkumar