A novel particle based approach for robust speech spectrum Vector Quantization

Vector quantization (VQ) has been extensively used in speech vocoders. The training process normally requires a very large training-set. This paper introduces a novel particle-based distortion measure for the high-band speech spectrum that enables the vector quantizer to operate given a relatively small training-set. This measure has been used in the construction of a segmental vocoder, which is using the pitch period as segments. A description of the proposed particle approach, the energy-mass distortion measure, is given. A comparison between the energy-mass and the use of the mel-frequency cepstral coefficients (MFCC) as a distortion measure shows the ability of the particle approach to better represent the speech formants, when operating under the small training-set constraint. Finally, the performance of the energy-mass is evaluated using the spectral distortion (SD). Speech quality perceived by the receiver is evaluated using the recently standardized objective quality measure PESQ where an improvement of 0.3 PESQ score was obtained.