Öz
This paper examines the behavior of two different energy-based voice activity detector (VAD) algorithms for noisy input signals. The examined detectors use time-domain methods to find speech boundaries. Time-domain short time energy features and/or zero-crossing rate of speech signals are used to evaluate the performance of the methods. In the first stage of both algorithms, time-domain short-time energy (STE) features are calculated for each speech segment. Then energy ratios and threshold values are used to detect any voicing activity of speech signals. The decision threshold value is calculated by evaluating the average STE of an initial silence period. The effectiveness of the selected methods is tested for clean and noisy speech samples. The methods are tested using the noisy speech signals under different SNR levels. The results indicated that both methods achieve a reasonable accuracy as low as an SNR value nearly 0dB with a slowly decreasing performance. But, under 0dB SNR, both methods lose their effectiveness against noisy conditions
Anahtar Kelimeler
Voice activity detection Speech analysis Speech/silence classification Endpoint detection Noise measurement
Kaynakça
- R. G. Bachu, S. Kopparthi, B. Adapa and B. D. Barkana (2010), Voiced/Unvoiced Decision for Speech Signals Based on Zero-Crossing Rate and Energy, January, 2010, Advanced Techniques in Computing Sciences and Software Engineering, pp 279-282, 2010; DOI 10.1007/978-90-481-3660-5_47
- K.Sakhnov, E.Verteletskaya and B. Simak (2009), Dynamical Energy-Based Speech/Silence Detector for Speech Enhancement Applications, Proceedings of the World Congress on Engineering 2009 Vol I, WCE 2009, July 1 - 3, London, U.K., ISBN: 978-988-17012-5-1 L. R. Rabiner ; M. R. Sambur (1975), An algorithm for determining the endpoints of isolated utterances, The Bell System Technical Journal ( Volume: 54 , Issue: 2 , Feb. 1975 ), (ISSN: 0005-8580), DOI: 10.1002/j.1538-7305.1975.tb02840.x, pp. 297 – 315,
- Prasad, V. (2002), Comparison of voice activity detection algorithms for VoIP, Proceedings - International Symposium on Computers and Communications, ·DOI: 10.1109/ISCC.2002.1021726, pp.62-65,
- Pollak, P., Sovka, P., Uhlir, J. (1993), Noise Suppression System for a Car, proc. of the Third European Conference on Speech, Communication and Technology – EUROSPEECH’93, (Berlin, Germany), p. 1 073–1 076, vol.5, Sept..
- A. M. Kondoz (1999), Digital Speech. New York: John Wiley and Sons,
- L. R. Rabiner and R. W. Schafer (2007), Introduction to Digital Speech Processing, Foundations and Trends in Signal Processing. Boston: Now Publishers Inc.,
- P.Renevey, A.Drygajlo, (2001), Entropy based voice activity detection in very noisy conditions, in Proc. Eurospeech 2001, pp.1887-1890
Enerji Tabanlı Konuşma Aktivitesi Belirleme Algoritmalarının Gürültülü Konuşma Sinyalleri için İncelenmesi
Öz
Anahtar Kelimeler
Konuşma Aktivite belirleme Konuşma analizi Konuşma/sessiz bölge sınıflandırma Sınır değer belirleme Gürültü hesaplama
Kaynakça
- R. G. Bachu, S. Kopparthi, B. Adapa and B. D. Barkana (2010), Voiced/Unvoiced Decision for Speech Signals Based on Zero-Crossing Rate and Energy, January, 2010, Advanced Techniques in Computing Sciences and Software Engineering, pp 279-282, 2010; DOI 10.1007/978-90-481-3660-5_47
- K.Sakhnov, E.Verteletskaya and B. Simak (2009), Dynamical Energy-Based Speech/Silence Detector for Speech Enhancement Applications, Proceedings of the World Congress on Engineering 2009 Vol I, WCE 2009, July 1 - 3, London, U.K., ISBN: 978-988-17012-5-1 L. R. Rabiner ; M. R. Sambur (1975), An algorithm for determining the endpoints of isolated utterances, The Bell System Technical Journal ( Volume: 54 , Issue: 2 , Feb. 1975 ), (ISSN: 0005-8580), DOI: 10.1002/j.1538-7305.1975.tb02840.x, pp. 297 – 315,
- Prasad, V. (2002), Comparison of voice activity detection algorithms for VoIP, Proceedings - International Symposium on Computers and Communications, ·DOI: 10.1109/ISCC.2002.1021726, pp.62-65,
- Pollak, P., Sovka, P., Uhlir, J. (1993), Noise Suppression System for a Car, proc. of the Third European Conference on Speech, Communication and Technology – EUROSPEECH’93, (Berlin, Germany), p. 1 073–1 076, vol.5, Sept..
- A. M. Kondoz (1999), Digital Speech. New York: John Wiley and Sons,
- L. R. Rabiner and R. W. Schafer (2007), Introduction to Digital Speech Processing, Foundations and Trends in Signal Processing. Boston: Now Publishers Inc.,
- P.Renevey, A.Drygajlo, (2001), Entropy based voice activity detection in very noisy conditions, in Proc. Eurospeech 2001, pp.1887-1890
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Mühendislik |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 31 Ekim 2019 |
| Yayımlandığı Sayı | Yıl 2019 Özel Sayı 2019 |
