完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.author | Huang, Feng-Long | |
| dc.contributor.author | Wang, Chan-Hsing | |
| dc.contributor.author | Yu, Ming-Shing | |
| dc.contributor.author | Wu, Min-Xiong | |
| dc.contributor.author | Lai, Yan-Kai | |
| dc.date.accessioned | 2009-06-02T07:06:25Z | |
| dc.date.accessioned | 2020-05-25T06:47:24Z | - |
| dc.date.available | 2009-06-02T07:06:25Z | |
| dc.date.available | 2020-05-25T06:47:24Z | - |
| dc.date.issued | 2009-02-12T03:33:58Z | |
| dc.date.submitted | 2009-02-12 | |
| dc.identifier.uri | http://dspace.lib.fcu.edu.tw/handle/2377/11221 | - |
| dc.description.abstract | In this paper, we describe the speaker independent speech recognition of Chinese number speeches 0~9 based on HMM. 560 speech samples are recorded and processed. The results of inside and outside testing achieve 92.5% and 76.79%, respectively. Furthermore, to improve the performance, two important features of speech; MFCC and cluster number of vector quantification, are unified and evaluated with various values. The best performance achieve 96%and 81% on MFCC Number = 20 and VQ clustering number = 64. | |
| dc.description.sponsorship | 淡江大學，台北縣 | |
| dc.format.extent | 6p. | |
| dc.relation.ispartofseries | 2008 ICS會議 | |
| dc.subject | Speech Recognition | |
| dc.subject | Hidden Markov Model | |
| dc.subject | LBG Algorithm | |
| dc.subject | Mel-frequency cepstral coefficients | |
| dc.subject | Viterbi Algorithm | |
| dc.subject.other | Artificial Intelligence | |
| dc.title | Speaker Independent Recognition of Chinese Number Speeches Based on Hidden Markov Model | |
| 分類: | 2008年 ICS 國際計算機會議 | |
文件中的檔案：
| 檔案 | 描述 | 大小 | 格式 | |
|---|---|---|---|---|
| ce07ics002008000159.pdf | 698.25 kB | Adobe PDF | 檢視/開啟 |
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