Speech activity detection on youtube using deep neural networks

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn , Issue , 2013, Pages 728-731

  Ryant, Neville ^a   Liberman, Mark ^a   Yuan, Jiahong ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Deep neural networks; Segmentation; Speech activity detection; Voice activity detection

Indexed keywords

IMAGE SEGMENTATION; SPEECH RECOGNITION;

CEPSTRAL FEATURES; DEEP NEURAL NETWORKS; ENVIRONMENTAL CONDITIONS; GAUSSIAN MIXTURE MODEL (GMMS); MEL-FREQUENCY CEPSTRAL COEFFICIENTS; SPEECH ACTIVITY DETECTIONS; STATIONARY NOISE; VOICE ACTIVITY DETECTION;

SPEECH PROCESSING;

EID: 84906228076     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. N. Morgan, D. Baron, J. Edwards, D. Ellis, D. Gelbart, A. Janin, T. Pfau, E. Shriberg, and A. Stolcke, "The Meeting Project at ICSI, " in Proceedings of the First International Conference on Human Language Technology Research, 2001, pp. 1-7.
2. T. Pfau, D. P. Ellis, and A. Stolcke, "Multispeaker Speech Activity Detection for the ICSI Meeting Recorder, " in Proceedings of Automatic Speech Recognition and Understanding, 2001, pp. 107-110.
3. D. A. Reynolds, "An overview of automatic speaker recognition technology, " in Proceedings of ICASSP, vol. 4, 2002, pp. 4072- 4075.
4. S. Sadjadi and J. Hansen, "Unsupervised speech activity detection using voicing measures and perceptual spectral flux, " Signal Processing Letters, IEEE, vol. 20, pp. 197-200, 2013.
5. N. Mesgarani, M. Slaney, and S. A. Shamma, "Discrimination of speech from nonspeech based on multiscale spectro-temporal modulations, " Audio, Speech, and Language Processing, IEEE Transactions on, vol. 14, no. 3, pp. 920-930, 2006.
6. T. Ng, B. Zhang, L. Nguyen, S. Matsoukas, K. Vesely, P. Matejka, X. Zhu, and N. Mesgarani, "Developing a speech activity detection system for the DARPA RATS program, " in Proceedings of InterSpeech, 2012.
7. A. Saito, Y. Nankaku, A. Lee, and K. Tokuda, "Voice activity detection based on conditional random fields using multiple features, " in Proceedings of InterSpeech, 2010, pp. 2086-2089.
8. P. Clement, T. Bazillon, and C. Fredouille, "Speaker diarization of heterogeneous web video files: A preliminary study, " in Proceedings of ICASSP, 2011, pp. 4432-4435.
9. A. Misra, "Speech/nonspeech segmentation in web videos, " in Proceedings of InterSpeech, 2012.
10. G. E. Hinton, S. Osindero, and Y.-W. Teh, "A fast learning algorithm for deep belief nets, " Neural Computation, vol. 18, no. 7, pp. 1527-1554, 2006.
11. S. Strassel, A. Morris, J. Fiscus, C. Caruso, H. Lee, P. Over, J. Fiumara, B. Shaw, B. Antonishek, and M. Michel, "Creating HAVIC: Heterogeneous Audio Visual Internet Collection, " in Proceedings of the Eight International Conference on Language Resources and Evaluation, 2012.
12. M. L. Glenn, S. M. Strassel, and H. Lee, "XTrans: A speech annotation and transcription tool, " Proceedings of InterSpeech, 2009.
13. J. Fiscus, N. Radde, J. Garofolo, A. Le, J. Ajot, and C. Laprun, "The Rich Transcription 2005 Spring Meeting Recognition Evaluation, " Machine Learning for Multimodal Interaction, pp. 369- 389, 2006.
14. J. Ramirez, J. C. Segura, C. Benitez, L. Garcia, and A. Rubio, "Statistical voice activity detection using a multiple observation likelihood ratio test, " Signal Processing Letters, IEEE, vol. 12, no. 10, pp. 689-692, 2005.
15. V. Nair and G. E. Hinton, "Rectified linear units improve restricted boltzmann machines, " in Proc. 27th International Conference on Machine Learning, 2010, pp. 807-814.
16. G. E. Dahl, D. Yu, L. Deng, and A. Acero, "Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition, " Audio, Speech, and Language Processing, IEEE Transactions on, vol. 20, no. 1, pp. 30-42, 2012.