SPEAKER-DEPENDENT-FEATURE EXTRACTION, RECOGNITION AND PROCESSING TECHNIQUES

This paper discusses recent advances in and perspectives of research on speaker-dependent-feature extraction from speech waves, automatic speaker identification and verification, speaker adaptation in speech recognition, and voice conversion techniques. Speaker-dependent information exists both in the spectral envelope and in the supra-segmental features of speech. This individual information can be further classified into temporal and dynamic features. Speaker identification/verification methods can be divided into text-dependent and text-independent methods. Although text-dependent speaker verification techniques have almost reached the level suitable for practical implementation, text-independent techniques are still in the fundamental research stage. Both supervised and unsupervised speaker adaptation algorithms for speech recognition have recently been proposed, and remarkable progress has been achieved in this field. Improving synthesized speech quality by adding natural characteristics of voice individuality, and converting synthesized voice individuality from one speaker to another, are as yet little exploited research fields to be studied in the near future. Research on speaker-dependent information is one of the most important future directions for achieving advanced speech information processing systems.