A Comparison Between STRAIGHT, Glottal, an Sinusoidal Vocoding in Statistical Parametric Speech Synthesis

Manu Airaksinen, Lauri Juvela, Bajibabu Bollepalli, Junichi Yamagishi, Paavo Alku

Research output: Contribution to journalArticlepeer-review

Abstract

A vocoder is used to express a speech waveform with a controllable parametric representation that can be converted back into a speech waveform. Vocoders representing their main categories (mixed excitation, glottal, sinusoidal vocoders) were compared in this study with formal and crowd-sourced listening tests. Vocoder quality was measured within the context of analysis-synthesis as well as text-to-speech (TTS) synthesis in a modern statistical parametric speech synthesis framework. Furthermore, the TTS experiments were divided into synthesis with vocoder-specific features and synthesis with a shared envelope model, where the waveform generation method of the vocoders is mainly responsible for the quality differences. Finally, all of the tests included four distinct voices as a way to investigate the effect of different speakers on the synthesized speech quality.
The obtained results suggest that the choice of the voice has a profound impact on the overall quality of the vocodergenerated speech, and the best vocoder for each voice can vary case by case. The single best-rated TTS system was obtained with the glottal vocoder GlottDNN using a male voice with low expressiveness. However, the results indicate that the sinusoidal vocoder PML (pulse model in log-domain) has the best overall performance across the performed tests. Finally, when controlling for the spectral models of the vocoders, the observed differences are similar to the baseline results. This indicates that the waveform generation method of a vocoder is essential for quality improvements.
Index Terms—Speech synthesis, vocoder, statistical parametric speech synthesis.
Original languageEnglish
Pages (from-to)1658-1670
Number of pages13
JournalIEEE/ACM Transactions on Audio, Speech and Language Processing
Volume26
Issue number9
Early online date11 May 2018
DOIs
Publication statusE-pub ahead of print - 11 May 2018

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