A Mandarin phrase recognition system based on MFCC, LPC scaled excitation, vowel model, hidden Markov model (HMM) and Viterbi algorithm is proposed in this thesis. HMM, which is broadly used in speech recognition at present, is adopted in the main structure of recognition. In order to speed up the recognition time, we take advantage of stability of vowels in Mandarin and incorporate with vowel class recognition in our system. For the speaker-dependent case, a single Mandarin phrase recognition can be accomplished within 1 seconds on average in the laboratory environment.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0902105-225405 |
Date | 02 September 2005 |
Creators | Pan, Ruei-tsz |
Contributors | Chii-Maw Uang, Tsung Lee, Chih-Chien Chen |
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-0902105-225405 |
Rights | not_available, Copyright information available at source archive |
Page generated in 0.0016 seconds