A design of speech recognition system for Chinese names has been established in this thesis. By identifying surname first, that is an unique feature of the Chinese names, the classification accuracy and computational time of the system can be greatly improved.
This research is primarily based on hidden Markov model (HMM), a technique that is widely used in speech recognition. HMM is a doubly stochastic process describing the ways of pronumciation by recording the state transitions according to the time-varing properties of the speech signal. The results of the HMM are compared with those of the segmental probability model (SPM) to figure out better option in recognizing base-syllables. Under the conditions of equal segments, SPM not only suits Mandarin base-syllable structure, but also achieves the goal of simplifying system since it does not need to find the best transformation of the utterance.
A speaker-independent 3000 Chinese names recognition system has been implemented based on the Mandarin microphone database recorded in the laboratory environment.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0811103-125211 |
| Date | 11 August 2003 |
| Creators | Chen, Yu-Te |
| Contributors | Chih-Chien Chen, Chii-Maw Uang, Tsung Lee |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0811103-125211 |
| Rights | not_available, Copyright information available at source archive |
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