Continuous speech speaker recognition based on CNN
In the last few years, with the constant improvement of the social life level, the requirement for speech recognition is getting higher and higher. GMM-HMM (Gaussian mixture-hidden Markov model) have been the main method for speaker recognition. Because of the bad modeling capability of big data and...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2017-03-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017046/ |
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| author | Zhendong WU Shucheng PAN Jianwu ZHANG |
| author_facet | Zhendong WU Shucheng PAN Jianwu ZHANG |
| author_sort | Zhendong WU |
| collection | DOAJ |
| description | In the last few years, with the constant improvement of the social life level, the requirement for speech recognition is getting higher and higher. GMM-HMM (Gaussian mixture-hidden Markov model) have been the main method for speaker recognition. Because of the bad modeling capability of big data and the bad performance of robustness, the development of this model meets the bottleneck.In order to solve this question, researchers began to focus on deep learning technologies. CNN deep learning model for continuous speech speaker recognition was introduced and CSR-CNN model was put forward. The model extracts fixed-length and right-order phonetic fraction to form an ordered sound spectrograph. Then input the voiceprint extract from CNN model to a reward-penalty function to continuous measurement. Experimental results show that CSR-CNN model has very good recognition effectin continuous speech speaker recognition field. |
| format | Article |
| id | doaj-art-c990320a00ba4186bd66056b9d4a5e55 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2017-03-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-c990320a00ba4186bd66056b9d4a5e552025-01-15T03:25:30ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012017-03-0133596659804391Continuous speech speaker recognition based on CNNZhendong WUShucheng PANJianwu ZHANGIn the last few years, with the constant improvement of the social life level, the requirement for speech recognition is getting higher and higher. GMM-HMM (Gaussian mixture-hidden Markov model) have been the main method for speaker recognition. Because of the bad modeling capability of big data and the bad performance of robustness, the development of this model meets the bottleneck.In order to solve this question, researchers began to focus on deep learning technologies. CNN deep learning model for continuous speech speaker recognition was introduced and CSR-CNN model was put forward. The model extracts fixed-length and right-order phonetic fraction to form an ordered sound spectrograph. Then input the voiceprint extract from CNN model to a reward-penalty function to continuous measurement. Experimental results show that CSR-CNN model has very good recognition effectin continuous speech speaker recognition field.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017046/continuous speechsound spectrographGMM-HMMdeep learning |
| spellingShingle | Zhendong WU Shucheng PAN Jianwu ZHANG Continuous speech speaker recognition based on CNN Dianxin kexue continuous speech sound spectrograph GMM-HMM deep learning |
| title | Continuous speech speaker recognition based on CNN |
| title_full | Continuous speech speaker recognition based on CNN |
| title_fullStr | Continuous speech speaker recognition based on CNN |
| title_full_unstemmed | Continuous speech speaker recognition based on CNN |
| title_short | Continuous speech speaker recognition based on CNN |
| title_sort | continuous speech speaker recognition based on cnn |
| topic | continuous speech sound spectrograph GMM-HMM deep learning |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017046/ |
| work_keys_str_mv | AT zhendongwu continuousspeechspeakerrecognitionbasedoncnn AT shuchengpan continuousspeechspeakerrecognitionbasedoncnn AT jianwuzhang continuousspeechspeakerrecognitionbasedoncnn |