2017 INTERSPEECH INTERSPEECH 2017

Time-Domain Envelope Modulating the Noise Component of Excitation in a Continuous Residual-Based Vocoder for Statistical Parametric Speech Synthesis

Abstract

In this paper, we present an extension of a novel continuous residual-based vocoder for statistical parametric speech synthesis. Previous work has shown the advantages of adding envelope modulated noise to the voiced excitation, but this has not been investigated yet in the context of continuous vocoders, i.e. of which all parameters are continuous. The noise component is often not accurately modeled in modern vocoders (e.g. STRAIGHT). For more natural sounding speech synthesis, four time-domain envelopes (Amplitude, Hilbert, Triangular and True) are investigated and enhanced, and then applied to the noise component of the excitation in our continuous vocoder. The performance evaluation is based on the study of time envelopes. In an objective experiment, we investigated the Phase Distortion Deviation of vocoded samples. A MUSHRA type subjective listening test was also conducted comparing natural and vocoded speech samples. Both experiments have shown that the proposed framework using Hilbert and True envelopes provides high-quality vocoding while outperforming the two other envelopes.

🧭 Keyword Pioneer — excitation modeling
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio