Abstract: A method of (and concomitant computer software embodied on a non-transitory computer-readable medium for) generating speech comprising receiving a mel-frequency cepstrum employing a set of weighting functions, generating a pseudo-inverse of the set, reconstructing a speech waveform from the cepstrum and the pseudo-inverse, and outputting sound corresponding to the waveform. Also a corresponding method of (and concomitant computer software embodied on a non-transitory computer-readable medium for) encoding speech comprising receiving sounds comprising speech, computing mel-frequency cepstral coefficients from the sounds using a quantization method selected from the group consisting of non-uniform scalar quantization and vector quantization, and generating and storing codewords from the coefficients that permit recreation of the sounds.

Abstract: The present invention is a system and method for discriminating between human and synthetic speech. The method and system include memory for storing a speaker verification application, a communication network that receives from a client device a speech signal having one or more discriminating features, and a processor for executing instructions stored in memory. The execution of the instructions by the processor extracts the one or more discriminating features from the speech signal and classifies the speech signal as human or synthetic based on the extracted features.

Abstract: A speech enhancement method (and concomitant computer-readable medium comprising computer software encoded thereon) comprising receiving samples of a user's speech, determining mel-frequency cepstral coefficients of the samples, constructing a Gaussian mixture model of the coefficients, receiving speech from a noisy environment, determining mel-frequency cepstral coefficients of the noisy speech, estimating mel-frequency cepstral coefficients of clean speech from the mel-frequency cepstral coefficients of the noisy speech and from the Gaussian mixture model, and outputting a time-domain waveform of enhanced speech computed from the estimated mel-frequency cepstral coefficients.

Abstract: A signal processing method and apparatus including a digital finite impulse response filter wherein the error caused by slow asymptotic convergence of the filter's adaptive coefficients is reduced. A first input signal is provided to an adaptive FIR filter including a coefficient calculator, finite impulse response FIR filter and a summation device. The filter also receives a second input signal, which may, for example, be the echo of the first input signal. The first input signal and the second input signal have a first bandwidth. The adaptive FIR filter then provides an output signal to a filter, which then filters the output signal to a second bandwidth which is less than the first bandwidth. The processed signal will have less error caused by the slow asymptotic convergence of the filter than previously possible because the error-concentrated frequency components near the band edge of the first frequency band have been filtered or removed.