Speech signals have been a research topic for over 50 years. However, many research and engineering challenges are still presented in a field of speech modeling and synthesis.
Speech parameterization techniques that are able, on the one hand to reconstruct a signal transparently, and on the other hand to modify it (in the parametric domain) are very important for flexible speech synthesis and advanced speech transformations (such as voice morphing, emotion modification etc.
This project deals with understanding different approaches for speech analysis and synthesis such as the sinusoidal model (SM), harmonic model (HM), and the adaptive harmonic model (aHM). Informal listening tests show that aHM achieves the best synthesized quality than the other examined methods.
Slava Shechtman IBM R&D labs