Multilingual text analysis for text-to-speech synthesis

Author:

SPROAT RICHARD

Abstract

We present a model of text analysis for text-to-speech (TTS) synthesis based on (weighted) finite state transducers, which serves as the text analysis module of the multilingual Bell Labs TTS system. The transducers are constructed using a lexical toolkit that allows declarative descriptions of lexicons, morphological rules, numeral-expansion rules, and phonological rules, inter alia. To date, the model has been applied to eight languages: Spanish, Italian, Romanian, French, German, Russian, Mandarin and Japanese.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics,Software

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multi-Task Learning for Front-End Text Processing in TTS;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Bangla text normalization for text-to-speech synthesizer using machine learning algorithms;Journal of King Saud University - Computer and Information Sciences;2024-01

3. Efficient Text Analysis with Pre-Trained Neural Network Models;2022 IEEE Spoken Language Technology Workshop (SLT);2023-01-09

4. Non-Standard Vietnamese Word Detection and Normalization for Text–to–Speech;2022 14th International Conference on Knowledge and Systems Engineering (KSE);2022-10-19

5. Finite-State Text Processing;Synthesis Lectures on Human Language Technologies;2021-05-26

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