Conferencia
Lei, Y.; Ferrer, L.; McLaren, M.; Scheffer, N.; Chng E.S.; Li H.; Meng H.; Ma B.; Xie L.; Amazon; Baidu; et al.; Google; Temasek Laboratories at Nanyang Technological University (TL at NTU); WeChat "A deep neural network speaker verification system targeting microphone speech" (2014) 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014:681-685
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Abstract:
We recently proposed the use of deep neural networks (DNN) in place of Gaussian Mixture models (GMM) in the i-vector extraction process for speaker recognition. We have shown significant accuracy improvements on the 2012 NIST speaker recognition evaluation (SRE) telephone conditions. This paper explores how this framework can be effectively used on the microphone speech conditions of the 2012 NIST SRE. In this new framework, the verification performance greatly depends on the data used for training the DNN. We show that training the DNN using both telephone and microphone speech data can yield significant improvements. An in-depth analysis of the influence of telephone speech data on the microphone conditions is also shown for both the DNN and GMM systems. We conclude by showing that the the GMM system is always outperformed by the DNN system on the telephone-only and microphone-only conditions, and that the new DNN / i-vector framework can be successfully used providing a good match in the training data. Copyright © 2014 ISCA.
Registro:
| Documento: | Conferencia |
| Título: | A deep neural network speaker verification system targeting microphone speech |
| Autor: | Lei, Y.; Ferrer, L.; McLaren, M.; Scheffer, N.; Chng E.S.; Li H.; Meng H.; Ma B.; Xie L.; Amazon; Baidu; et al.; Google; Temasek Laboratories at Nanyang Technological University (TL at NTU); WeChat |
| Filiación: | Speech Technology and Research Laboratory, SRI InternationalCA, United States Departamento de Computacíon, FCEN, Universidad de Buenos Aires, Argentina |
| Palabras clave: | Deep neural networks; I-vectors; Microphone data; Speaker recognition; Microphones; Speech; Speech communication; Telephone sets; Accuracy Improvement; Deep neural networks; Gaussian Mixture Model; I-vectors; In-depth analysis; Speaker recognition; Speaker recognition evaluations; Speaker verification system; Speech recognition |
| Año: | 2014 |
| Página de inicio: | 681 |
| Página de fin: | 685 |
| Título revista: | 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 |
| Título revista abreviado: | Proc. Annu. Conf. Int. Speech. Commun. Assoc., INTERSPEECH |
| ISSN: | 2308457X |
| Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei |
Referencias:
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- Lei, Y., Scheffer, N., Ferrer, L., Mclaren, M., A novel scheme for speaker recognition using a phoneticallyaware deep neural network (2007) ICASSP-2014, , IEEE
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- NIST SRE12 Evaluation Plan, , http://www.nist.gov/itl/iad/mig/upload/NISTSRE12evalplanv11-r0.pdf
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- Deng, L., Li, J., Huang, J., Yao, K., Yu, D., Seide, F., Seltzer, M., Acero, A., Recent advances in deep learning for speech research at Microsoft (2013) ICASSP-2013, pp. 8604-8608. , IEEEA4 - Amazon; Baidu; et al.; Google; Temasek Laboratories at Nanyang Technological University (TL at NTU); WeChat
Citas:
---------- APA ----------
Lei, Y., Ferrer, L., McLaren, M., Scheffer, N., Chng E.S., Li H., Meng H.,..., Amazon; Baidu; et al.; Google; Temasek Laboratories at Nanyang Technological University (TL at NTU); WeChat (2014) . A deep neural network speaker verification system targeting microphone speech. 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014, 681-685.Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei [ ]
---------- CHICAGO ----------
Lei, Y., Ferrer, L., McLaren, M., Scheffer, N., Chng E.S., Li H., et al. "A deep neural network speaker verification system targeting microphone speech" . 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 (2014) : 681-685.Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei [ ]
---------- MLA ----------
Lei, Y., Ferrer, L., McLaren, M., Scheffer, N., Chng E.S., Li H., et al. "A deep neural network speaker verification system targeting microphone speech" . 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014, 2014, pp. 681-685.Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei [ ]
---------- VANCOUVER ----------
Lei, Y., Ferrer, L., McLaren, M., Scheffer, N., Chng E.S., Li H., et al. A deep neural network speaker verification system targeting microphone speech. Proc. Annu. Conf. Int. Speech. Commun. Assoc., INTERSPEECH. 2014:681-685.Available from: https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_2308457X_v_n_p681_Lei [ ]
