Abstract
Automatic detection of shout in continuous speech is a challenging task. In our recent study, the characteristics of shout and normal speech signals are examined along with the electroglottograph (EGG) signals. The study highlights the changes in the characteristics of both the excitation source and the vocal tract system during production of shout, from those of normal speech. In this paper, we aim to develop an automatic system to detect regions of shout in continuous speech, based upon changes in the production characteristics of shouted speech. Discriminating production features like instantaneous fundamental frequency, strength of excitation, dominant frequency and spectral band energy ratio are extracted from the speech signal. Parameters are derived for the shout decision capturing average level and temporal changes in the features and their pairwise mutual relations. A speaker and language independent prototype automatic shout detection system is developed. Performance evaluation over four databases gave encouraging results.
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References
Nanjo, H., Nishiura, T., Kawano, H.: Acoustic-based security system: towards robust understanding of emergency shout. In: Proceedings of the Fifth International Conference on Information Assurance and Security, 2009 (IAS 2009), August 2009, vol. 1, pp. 725–728 (2009)
Huang, W., Chiew, T.K., Li, H., Kok, T.S., Biswas, J.: Scream detection for home applications. In: Proceedings of the 5th IEEE Conference on Industrial Electronics and Applications, 2010 (ICIEA 2010), June 2010, pp. 2115–2120 (2010)
Rouas, J.L., Louradour, J., Ambellouis, S.: Audio events detection in public transport vehicle. In: Proceedings of the IEEE Intelligent Transportation Systems Conference, 2006 (ITSC 2006), September 2006, 733–738 (2006)
Van Hengel, P.W.J., Andringa, T.C.: Verbal aggression detection in complex social environments. In Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2007 (AVSS 2007), September 2007, pp. 15–20 (2007)
Valenzise, G., Gerosa, L., Tagliasacchi, M., Antonacci, F., Sarti, A.: Scream and gunshot detection and localization for audio-surveillance systems. In: Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2007 (AVSS 2007), September 2007, pp. 21–26 (2007)
Pohjalainen, J., Alku, P., Kinnunen, T.: Shout detection in noise. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2011 (ICASSP 2011), May 2011, pp. 4968–4971 (2011)
Zelinka, P., Sigmund, M., Schimmel, J.: Impact of vocal effort variability on automatic speech recognition. Speech Commun. 54(6), 732–742 (2012)
Pohjalainen, J., Raitio, T., Yrttiaho, S., Alku, P.: Detection of shouted speech in noise: human and machine. J. Acoust. Soc. Am. 133(4), 2377–2389 (2013)
Mittal, V.K., Yegnanarayana, B.: Effect of glottal dynamics in the production of shouted speech. J. Acoust. Soc. Am. 133(5), 3050–3061 (2013)
Mittal, V.K., Yegnanarayana, B.: Production features for detection of shouted speech. In: Proceedings of the 10th IEEE CCNC 2013, USA, 11–14 January 2013, pp. 106–111 (2013)
Fant, G., Lin, Q., Gobl, C.: Notes on glottal flow interaction. STL-QPSR, KTH, Sweden 26(2–3), 21–45 (1985)
Murty, K.S.R., Yegnanarayana, B.: Epoch extraction from speech signals. IEEE Trans. Audio Speech Lang. Process. 16(8), 1602–1613 (2008)
Makhoul, J.: Linear prediction: a tutorial review. Proc. IEEE 63, 561–580 (1975)
Yegnanarayana, B., Murty, K.S.R.: Event-based instantaneous fundamental frequency estimation from speech signals. IEEE Trans. Audio Speech Lang. Process. 17(4), 614–624 (2009)
Gangamohan, P., Kadiri, S.R., Yegnanarayana, B.: Analysis of emotional speech at subsegmental level. In: Proceedings of International Conference on Spoken Language Processing (INTERSPEECH), Lyon, France, 25-29 August 2013, pp. 1916–1920 (2013)
Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W., Weiss, B.: A database of German emotional speech. In: Proceedings of International Conference on Spoken Language Processing (INTERSPEECH), pp. 1517–1520. ISCA, Lisbon, Portugal, 4–8 September 2005
Zhang, C., Hansen, J.H.L.: Analysis and classification of speech mode: whispered through shouted, In: Proceedings of International Conference on Spoken Language Processing (INTERSPEECH), pp. 2289–2292. ISCA, Antwerp, Belgium (2007)
Acknowledgement
This work is partially supported by research collaboration between Speech Vision Laboratory, IIIT, Hyderabad and SAIT, SRI, Bangalore (2010-2013).
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Mittal, V.K., Yegnanarayana, B. (2015). An Automatic Shout Detection System Using Speech Production Features. In: Böck, R., Bonin, F., Campbell, N., Poppe, R. (eds) Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction. MA3HMI 2014. Lecture Notes in Computer Science(), vol 8757. Springer, Cham. https://doi.org/10.1007/978-3-319-15557-9_9
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DOI: https://doi.org/10.1007/978-3-319-15557-9_9
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