Abstract
Gender-dependent (male/female) acoustic models are more acoustically homogeneous and therefore give better recognition performance than single gender-independent model. This paper deals with a problem how to use these gender-based acoustic models in a real-time LVCSR (Large Vocabulary Continuous Speech Recognition) system that is for more than one year used by the Czech TV for automatic subtitling of Parliament meetings that are broadcasted on the channel ČT24. Frequent changes of speakers and the direct connection of the LVCSR system to the TV audio stream require switching/fusion of models automatically and as soon as possible. The paper presents various techniques based on using the output probabilities for quick selection of a better model or their combinations. The best proposed method achieved over 11% relative WER reduction in comparision with the GI model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Pražák, A., Psutka, J., Hoidekr, J., Kanis, J., Müller, L., Psutka, J.: Automatic Online Subtitling of the Czech Parliament Meetings. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2006. LNCS (LNAI), vol. 4188, pp. 501–508. Springer, Heidelberg (2006)
Olsen, P. A., Dharanipragada, S.: An Efficient Integrated Gender Detection Scheme and Time Mediated Averaging of Gender Dependent Acoustic Models. In: 8th European Conference on Speech Communication and Technology (EUROSPEECH 2003), Geneva, Switzerland (2003)
Neto, J., Meinedo, H., Viveiros, M., Cassaca, R., Martins, C., Caseiro, D.: Broadcast News Subtitling System in Portuguese. In: Proceedings of the ICASSP, Las Vegas, USA (2008)
Radová, V., Psutka, J.: UWB-S01 Corpus: A Czech Read-Speech Corpus. In: Proceedings of the 6th International Conference on Spoken Language Processing ICSLP 2000, Beijing, China (2000)
Psutka, J., Müller, L., Psutka, J. V.: Comparison of MFCC and PLP Parameterization in the Speaker Independent Continuous Speech Recognition Task. In: 7th European Conference on Speech Communication and Technology (EUROSPEECH 2001), Aalborg, Denmark (2001)
Hermansky, H.: Perceptual Linear Predictive (PLP) Analysis of Speech. J. Acoustic. Soc. Am. 87 (1990)
Psutka, J.: Robust PLP-Based Parameterization for ASR Systems. In: SPECOM 2007 Proceedings. Moscow State Linguistic University, Moscow (2007)
Young, S., et al.: The HTK Book (for HTK Version 3.4), Cambridge (2006)
Vaněk, J., Psutka, J.V., Zelinka, J., Pražák, A., Psutka, J.: Discriminative Training of Gender-Dependent Acoustic Models. In: Matoušek, V., Mautner, P. (eds.) TSD 2009. LNCS (LNAI), vol. 5729, pp. 331–338. Springer, Heidelberg (2009)
Vanek J.: Discriminative Training of Acoustic Models. Ph.D. Thesis, West Bohemia University, Department of Cybernetics (2009) (in Czech)
Stolcke, A.: SRILM – An Extensible Language Modeling Toolkit. In: International Conference on Spoken Language Processing (ICSLP 2002), Denver, USA (2002)
Pražák, A., Ircing, P., Švec, J., et al.: Efficient Combination of N-gram Language Models and Recognition Grammars in Real-Time LVCSR Decoder. In: 9th International Conference on Signal Processing, Beijing, China, pp. 587–591 (2008)
Pražák, A., Müller, L., Šmídl, L.: Real-Time Decoder for LVCSR System. In: 8th World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando FL, USA (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vaněk, J., Psutka, J.V. (2010). Gender-Dependent Acoustic Models Fusion Developed for Automatic Subtitling of Parliament Meetings Broadcasted by the Czech TV. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2010. Lecture Notes in Computer Science(), vol 6231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15760-8_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-15760-8_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15759-2
Online ISBN: 978-3-642-15760-8
eBook Packages: Computer ScienceComputer Science (R0)