Syntactic analysis and letter-to-phoneme conversion using neural networks — an application of neural networks to an english text-to-speech system

✍ Scribed by Yukiko Yamaguchi; Tatsuro Matsumoto

• Publisher: John Wiley and Sons
• Year: 1993
• Tongue: English
• Weight: 868 KB
• Volume: 24
• Category: Article
• ISSN: 0882-1666
• DOI: 10.1002/scj.4690240807

✦ Synopsis

Abstract

This paper presents a speech synthesis system using the neural network. While there have been a large number of speech synthesis systems developed, most of them are rule‐based systems for a restricted range of languages, describing the expert knowledges for the language in the form of rules. Thus problems arise in that a large amount of effort is required in developing the system, and the extension of other languages is not easy.

In the area of natural language processing, on the other hand, there are practical applications of machine translation, and it is desired that speech synthesis systems for various languages be developed in the future. From such a viewpoint, the authors developed the English speech synthesis system, aiming at the easy extension to multiple languages without requiring expert knowledge.

In this paper, the neural networks is applied to the part‐of‐speech detection function, the syntactic boundary detection function and the letter‐to‐phoneme conversion function, all of which have stronger language dependencies among the components of the speech synthesis system.