This thesis investigates the design and implementation strategies for a Spanish speech recognition system. It utilizes the speech features of the 242 common Spanish mono-syllables as the major training and recognition methodology. A training database of twelve utterances per mono-syllable is established by applying Spanish pronunciation rules. These twelve utterances are collected through reading six rounds of the same mono-syllable with two different tones. The first pronounced pattern has high pitch of tone one, while the second one has falling pitch of tone four. Mel-frequency cepstral coefficients, linear predictive cepstral coefficients, and hidden Markov model are used as the two feature models and the recognition model respectively. Under the AMD Sempron Processor 2800+ with 1.6GHz clock rate personal computer and Ubuntu 9.04 operating system environment, a correct phrase recognition rate of 86% can be reached for a 4217 Spanish phrase database. The average computation time for each phrase is about 1.5 seconds.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0824110-152713 |
| Date | 24 August 2010 |
| Creators | Shih, Shih-Jhou |
| Contributors | ER-HUI LU, Tsung Lee, XIAO-SONG BO, Chih-Chien Chen, Chii-Maw Uang |
| 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-0824110-152713 |
| Rights | not_available, Copyright information available at source archive |
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