Speech mode based multi-stage vector quantizer
First Claim
1. An encoder for use in encoding a signal for transmission in a communication system, comprising:
- a mode classifier that classifies the signal as being associated with one of a plurality of classes;
a converter that converts the signal into a first vector; and
a vector quantizer having a first multi-stage section that quantizes the vector according to a first quantization scheme when the signal is classified as being associated with a first one of the classes and a second multi-stage section that quantizes the vector according to a second quantization scheme when the signal is classified as being associated with a second one of the classes, the stages of the first multi-stage section being arranged in a first backward predictive network to reduce correlation between adjacent frames of the signal when the signal is classified as being associated with the first one of the classes, and the stages of the second multi-stage section being arranged in a second backward predictive network to reduce correlation between adjacent frames of the signal when the signal is classified as being associated with the second one of the classes.
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Abstract
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.
165 Citations
39 Claims
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1. An encoder for use in encoding a signal for transmission in a communication system, comprising:
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a mode classifier that classifies the signal as being associated with one of a plurality of classes; a converter that converts the signal into a first vector; and a vector quantizer having a first multi-stage section that quantizes the vector according to a first quantization scheme when the signal is classified as being associated with a first one of the classes and a second multi-stage section that quantizes the vector according to a second quantization scheme when the signal is classified as being associated with a second one of the classes, the stages of the first multi-stage section being arranged in a first backward predictive network to reduce correlation between adjacent frames of the signal when the signal is classified as being associated with the first one of the classes, and the stages of the second multi-stage section being arranged in a second backward predictive network to reduce correlation between adjacent frames of the signal when the signal is classified as being associated with the second one of the classes. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 28)
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13. A line spectral frequency (LSF) vector quantizer for use in encoding an LSF vector in a digital communication system, comprising:
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a mode classifier that classifies the LSF vector as being associated with one of a plurality of modes; a first multi-stage LSF vector quantizer section having multiple stages that quantize the LSF vector when the LSF vector is associated with a first one of the plurality of modes, the multiple stages of the first multi-stage section being arranged in a backward predictive network to reduce correlation between adjacent frames of a signal associated with the LSF vector when the LSF vector is associated with the first one of the plurality of modes; and a second LSF vector quantizer section having multiple stages that quantize the LSF vector when the LSF vector is associated with a second one of the plurality of modes, the multiple stages of the second multi-stage section being arranged in a backward predictive network to reduce correlation between adjacent frames of the signal associated with the LSF vector when the LSF vector is associated with the second one of the plurality of modes. - View Dependent Claims (14, 15, 16, 17, 18)
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19. A method of encoding a speech signal, comprising the steps of:
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dividing the speech signal into a series of speech frames; converting each of the speech frames into a vector; identifying a mode associated with each of the speech frames as a first mode or a second mode; encoding the vectors for the speech frames associated with the first mode using a first multi-stage LSF vector encoder including a first backward predictive network to reduce correlation between adjacent speech frames of the speech signal; and
,encoding the vectors for the speech frames associated with the second mode using a second multi-stage LSF vector encoder including a second backward predictive network to reduce correlation between adjacent speech frames of the speech signal. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27)
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29. For use with a receiver, a decoder for decoding a speech frame received by the receiver comprising:
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a demultiplexer for separating a received signal into a mode signal indicative of a mode of the speech frame to be decoded and a plurality of codebook addresses associated with the speech frame; and a vector decoder including a first set of codebooks for decoding codebook addresses associated with speech frames classified in a first mode, a second set of codebooks for decoding codebook addresses associated with speech frames classified in a second mode, a mode select unit responsive to the mode signal to route the codebook addresses to one of the first and second sets of codebooks depending on the mode of the speech frame, a summer for developing an overall quantized vector from one of the first and second sets of codebooks, and a correlation component network for adding a correlation component to the overall quantized vector to create a quantized differential vector. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39)
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Specification