Patent ID: 6219642
Filing Date: 2001-04-17
Classification: G10L

Abstract:
An apparatus comprising:a mean compensation module to receive parameters for TO samples of an input signal and to generate mean compensated parameters from the received input signal parameters;a first quantizer to receive the input signal parameters and to quantize the input signal parameters, wherein the first quantizer is comprised of a first matrix quantizer and a first vector quantizer;a second quantizer to receive the input signal mean compensated parameters and to quantize the input signal mean compensated parameters wherein the second quantizer is comprised of a second matrix quantizer and a second vector quantizer;a backend processor to receive the quantized input signal parameters and the input signal mean compensated input signal parameters and to classify the input signal therefrom, wherein the backend processor comprises:a first group of hidden Markov models which are trained using quantized input signal parameters from the first and second matrix quantizers;a second group of hidden Markov models which are trained using quantized input signal parameters from the first and second vector quantizers; anda stochastic module to (a) receive the quantized input signal parameters from the first and second matrix quantizers, (b) determine the respective probabilities that each hidden Markov model from the first group of hidden Markov models modeled the quantized input signal parameters from the first and second matrix quantizers, (c) receive the quantized input signal parameters from the first and second vector quantizers, (d) determine the respective probabilities that each hidden Markov model from the second group of hidden Markov models to have modeled the quantized input signal parameters from the first and second vector quantizers, wherein the backend processor is capable of utilizing the probabilities to generate the input signal classification.