Abstract: A method for encoding a digitized speech signal so as to generate data capable of being decoded as speech. A digitized speech signal is first converted to a series of feature vectors using for example known Mel-frequency Cepstral coefficients (MFCC) techniques. At successive instances instance of time a respective pitch value of the digitized speech signal is computed, and successive acoustic vectors each containing the respective pitch value and feature vector are compressed so as to derive therefrom a bit stream. A suitable decoder reverses the operation so as to extract the features vectors and pitch values, thus allowing speech reproduction and playback. In addition, speech recognition is possible using the decompressed feature vectors, with no impairment of the recognition accuracy and no computational overhead.

Abstract: A method for estimating a pitch frequency of an audio signal includes computing a first transform of the signal to a frequency domain over a first time interval, and computing a second transform of the signal to the frequency domain over a second time interval, which contains the first time interval. A line spectrum of the signal is found, based on the first and second transforms, the spectrum including spectral lines having respective line amplitudes and line frequencies. A utility function that is periodic in the frequencies of the lines in the spectrum is then computed. This function is indicative, for each candidate pitch frequency in a given pitch frequency range, of a compatibility of the spectrum with the candidate pitch frequency. The pitch frequency of the speech signal is estimated responsive to the utility function.

Abstract: A method for encoding a digitized speech signal so as to generate data capable of being decoded as speech. A digitized speech signal is first converted to a series of feature vectors using for example known Mel-frequency Cepstral coefficients (MFCC) techniques. At successive instances instance of time a respective pitch value of the digitized speech signal is computed, and successive acoustic vectors each containing the respective pitch value and feature vector are compressed so as to derive therefrom a bit stream. A suitable decoder reverses the operation so as to extract the features vectors and pitch values, thus allowing speech reproduction and playback. In addition, speech recognition is possible using the decompressed feature vectors, with no impairment of the recognition accuracy and no computational overhead.