| 講演抄録/キーワード |
| 講演名 |
2008-03-20 15:15
[ポスター講演]Improvement of robustness using selective sound segregation for automatic speech recognition systems in noisy environments ○Atsushi Haniu・Masashi Unoki・Masato Akagi(JAIST) SP2007-196 |
| 抄録 |
(和) |
This paper proposes the concept of our novel robust speech recognition method based on the selective sound segregation model, and demonstrates that the proposed method can play an effective role to improve robustness of automatic speech recognition (ASR) systems in various noisy environments. Almost all ASR systems for noise environments attempt to transform an input sound into a clean speech or reference patterns into ones adapted for noises using a noise model, and calculate similarity or dissimilarity between an input sound and reference patterns. In our proposed method, the existing probability of a target speech in an input sound is employed as a measure of recognition. The existing probability of a target speech is calculated by validity of the selective sound segregation model without any noise model. An ASR system employing our proposed method was implemented. To evaluate our proposed method, Japanese digit recognitions in various noisy environments were carried out using traditional ASR systems and the proposed one. The results show that the proposed method is more robust than other methods in experimental conditions in SNR = 0 dB. These indicate the proposed method can play an effective role to improve robustness of the ASR systems. |
| (英) |
This paper proposes the concept of our novel robust speech recognition method based on the selective sound segregation model, and demonstrates that the proposed method can play an effective role to improve robustness of automatic speech recognition (ASR) systems in various noisy environments. Almost all ASR systems for noise environments attempt to transform an input sound into a clean speech or reference patterns into ones adapted for noises using a noise model, and calculate similarity or dissimilarity between an input sound and reference patterns. In our proposed method, the existing probability of a target speech in an input sound is employed as a measure of recognition. The existing probability of a target speech is calculated by validity of the selective sound segregation model without any noise model. An ASR system employing our proposed method was implemented. To evaluate our proposed method, Japanese digit recognitions in various noisy environments were carried out using traditional ASR systems and the proposed one. The results show that the proposed method is more robust than other methods in experimental conditions in SNR = 0 dB. These indicate the proposed method can play an effective role to improve robustness of the ASR systems. |
| キーワード |
(和) |
Speech recognition / Noisy environment / Improving robustness / Bregman’s regularities / Selective sound segregation / / / |
| (英) |
Speech recognition / Noisy environment / Improving robustness / Bregman’s regularities / Selective sound segregation / / / |
| 文献情報 |
信学技報, vol. 107, no. 551, SP2007-196, pp. 57-62, 2008年3月. |
| 資料番号 |
SP2007-196 |
| 発行日 |
2008-03-13 (SP) |
| ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| PDFダウンロード |
SP2007-196 |