Registration for ICASSP is free of charge, but registration is required to view the videos. If you have not yet registered, please visit: https://cmsworkshops.com/ICASSP2020/Registration.asp.Access the full virtual conference by visiting: https://2020.ieeeicassp-virtual.org/attendee/login. Your username is your email address and your password is your confirmation number/registration ID.

You need an account to view media

Sign in to view media

Don't have an account? Please contact us to request an account.

Speech Processing
SPE-P19.9
Poster
Machine Learning for Speech Synthesis III

ESPNET-TTS: UNIFIED, REPRODUCIBLE, AND INTEGRATABLE OPEN SOURCE END-TO-END TEXT-TO-SPEECH TOOLKIT

Tomoki Hayashi

Date & Time

Fri, May 8, 2020

12:45 pm – 2:45 pm

Location

On-Demand

Abstract

This paper introduces a new end-to-end text-to-speech (E2E-TTS) toolkit named ESPnet-TTS, which is an extension of the open-source speech processing toolkit ESPnet. The toolkit supports state-of-the-art E2E-TTS models, including Tacotron~2, Transformer TTS, and FastSpeech, and also provides recipes inspired by the Kaldi automatic speech recognition (ASR) toolkit. The recipes are based on the design unified with the ESPnet ASR recipe, providing high reproducibility. The toolkit also provides pre-trained models and samples of all of the recipes so that users can use it as a baseline. Furthermore, the unified design enables the integration of ASR functions with TTS, e.g., ASR-based objective evaluation and semi-supervised learning with both ASR and TTS models. This paper describes the design of the toolkit and experimental evaluation in comparison with other toolkits. The experimental results show that our models can achieve state-of-the-art performance comparable to the other latest toolkits, resulting in a mean opinion score (MOS) of 4.25 on the LJSpeech dataset. The toolkit is publicly available at https://github.com/espnet/espnet.


Presenter

Tomoki Hayashi

Nagoya university
Sign in to join the conversationDon't have an account? Please contact us to request an account.
Sign in to view documentsDon't have an account? Please contact us to request an account.

Session Chairs

Mounya Elhilali

LCAP, Johns Hopkins University