Abstract: A method for speech synthesis includes receiving an input speech signal containing a set of speech segments, and estimating spectral envelopes of the input speech signal in a succession of time intervals during each of the speech segments. The spectral envelopes are integrated over a plurality of window functions in a frequency domain so as to determine elements of feature vectors corresponding to the speech segments. An output speech signal is reconstructed by concatenating the feature vectors corresponding to a sequence of the speech segments.

Abstract: A method for processing a speech signal includes dividing the speech signal into a succession of frames, identifying one or more of the frames as click frames, and extracting phase information from the click frames. The speech signal is encoded using the phase information. Methods are also provided for modeling phase spectra of voiced frames and click frames.

Abstract: A method for converting speech to text and vice versa. The method for converting speech to text includes receiving a spoken input having a non-verbal characteristic, and automatically generating a text output, responsive to the spoken input, having a variable format characteristic corresponding to the non-verbal characteristic of the spoken input. The method for converting text to speech includes receiving a text input having a given variable format characteristic and synthesizing speech corresponding to the text input and having a non-verbal characteristic corresponding to the variable format characteristic of the text input.

Abstract: A speech reconstruction method and system for converting a series of binned spectra or functions thereof such as the Mel Frequency Cepstra Coefficients (MFCC), of an original digitized speech signal, into a reconstructed speech signal, where each binned spectrum has a respective pitch value and voicing decision. The binned spectra are derived from the original digitized speech signal at successive instances by multiplying each estimate of the spectral envelope by a predetermined set of frequency domain window functions and computing the integrals thereof. At each respective time instance, harmonic frequencies and weights are generated according to the respective pitch value and voicing decision. Basis functions having bounded supports on the frequency axis are each sampled at all said harmonic frequencies, which are within its support and multiplied by respective harmonic weights.

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.

Abstract: A method for speech synthesis includes receiving an input speech signal containing a set of speech segments, and estimating spectral envelopes of the input speech signal in a succession of time intervals during each of the speech segments. The spectral envelopes are integrated over a plurality of window functions in a frequency domain so as to determine elements of feature vectors corresponding to the speech segments. An output speech signal is reconstructed by concatenating the feature vectors corresponding to a sequence of the speech segments.