Work

Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform

Year: 2018

Type: conference-paper

Abstract: We present a new workflow to create components for the MaryTTS text-to-speech synthesis platform, which is popular with researchers and developers, extending it to support new languages and custom synthetic voices. This workflow replaces the previous toolkit with an efficient, flexible process that leverages modern build automation and cloud-hosted infrastructure. Moreover, it is compatible with the updated MaryTTS architecture, enabling new features and state-of-the-art paradigms such as synthesis based on deep neural networks (DNNs). Like MaryTTS itself, the new tools are free, open source software (FOSS), and promote the use of open data.

Source: Language Resources and Evaluation Conference (LREC)

DOI: 10.63317/2s9w7jk4ompu

Authors: Ingmar Steiner, Sébastien Le Maguer

Institution: Saarland University

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Deutsche Forschungsgemeinschaft

Awards: G1951765764, G893193274