Improve recognition performance of limabeam algorithm using mllr adaptation for environment
This paper presents method using MLLR adaptation to improve recognition performance of Limabeam algorithm in speech recognition using microphone array for Korean database. From our investigation for this Limabeam, we could see that because the performance of filtering optimization depends strongly o...
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Trường Đại học Đà Lạt
2012
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| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/33633 |
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oai:scholar.dlu.edu.vn:DLU123456789-336332012-12-26T01:22:00Z Improve recognition performance of limabeam algorithm using mllr adaptation for environment Nguyen, Dinh Cuong Pham, The Hien Limabeam calibrate Limabeam algorithm MLLR adaptation This paper presents method using MLLR adaptation to improve recognition performance of Limabeam algorithm in speech recognition using microphone array for Korean database. From our investigation for this Limabeam, we could see that because the performance of filtering optimization depends strongly on the supporting optimal state sequence. This sequence was created by using Viterbi algorithm with HMM trained model. So the proposed approach is based on that we used MLLR adaptation for the utterance in new environment to obtain the better optimal state sequence that support for the filtering parameters optimal step. Experimental results showed that using MLLR adaptation embed into the system, we have got the word correct recognition rate 2% higher than that of original calibrate Limabeam also 7% higher compared to Delay and Sum algorithm. 2012-12-26T01:22:00Z 2012-12-26T01:22:00Z 2012 Working Paper https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/33633 en Kỷ yếu Hội thảo công nghệ thông tin 2012;tr. 59-67 application/pdf Trường Đại học Đà Lạt |
| institution |
Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
| language |
English |
| topic |
Limabeam calibrate Limabeam algorithm MLLR adaptation |
| spellingShingle |
Limabeam calibrate Limabeam algorithm MLLR adaptation Nguyen, Dinh Cuong Pham, The Hien Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| description |
This paper presents method using MLLR adaptation to improve recognition performance of Limabeam algorithm in speech recognition using microphone array for Korean database. From our investigation for this Limabeam, we could see that because the performance of filtering optimization depends strongly on the supporting optimal state sequence. This sequence was created by using Viterbi algorithm with HMM trained model. So the proposed approach is based on that we used MLLR adaptation for the utterance in new environment to obtain the better optimal state sequence that support for the filtering parameters optimal step.
Experimental results showed that using MLLR adaptation embed into the system, we have got the word correct recognition rate 2% higher than that of original calibrate Limabeam also 7% higher compared to Delay and Sum algorithm. |
| format |
Working Paper |
| author |
Nguyen, Dinh Cuong Pham, The Hien |
| author_facet |
Nguyen, Dinh Cuong Pham, The Hien |
| author_sort |
Nguyen, Dinh Cuong |
| title |
Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| title_short |
Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| title_full |
Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| title_fullStr |
Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| title_full_unstemmed |
Improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| title_sort |
improve recognition performance of limabeam algorithm using mllr adaptation for environment |
| publisher |
Trường Đại học Đà Lạt |
| publishDate |
2012 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/33633 |
| _version_ |
1819791273918201856 |