A Mandarin Dictation Machine Based Upon a Hierarchical Recognition Approach and Chinese Natural Language Analysis

Abstract

An experimental Mandarin dictation machine for inputting Mandarin speech (spoken Chinese language) into computers is described. Because of the special characteristics of the Chinese language, syllables are chosen as the basic units for dictation. The machine is designed based on a hierarchical language recognition approach in which acoustic signals are first recognized as a sequence of syllables, possible word hypotheses are then formed from the syllables, and the complete sentences are finally obtained. This approach is implemented by two subsystems. The first recognizes the syllables using speech signal processing techniques, the second subsystem then identifies the exact characters from the syllable and corrects the errors in syllable recognition. The detailed syllable recognition algorithms, word formation rules, parser, grammar, and the syntactic checking algorithms are described. With newspaper text in the form of isolated syllables as input, the preliminary test results indicate that such a dictation machine is not only practically attractive, but technically feasible.