Abstract
Computerized systems with voice user interfaces could save time and ease the work of healthcare practitioners. To achieve this goal voice user interface should be reliable (to recognize the commands with high enough accuracy) and properly designed (to be convenient for the user). The paper deals with hybrid approach implementation issues for the voice commands recognition. By the hybrid approach we assume the combination of several different recognition methods to achieve higher recognition accuracy. The experimental results show that most voice commands are recognized good enough but there is some set of voice commands which recognition is more complicated. In this paper the novel method is proposed for the combination of several recognition methods based on the Ripper algorithm. Experimental evaluation showed that this method allows achieve higher recognition accuracy than application of blind combination rule.
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
Suendermann, D., Pieraccini, R.: SLU in Commercial and Research Spoken Dialogue Systems. In: Tur, G., De Mori, R. (eds.) Spoken Language Understanding, pp. 171–194. John Wiley & Sons, Ltd. (2011)
Rudzionis, V., Ratkevicius, K., Rudzionis, A., Maskeliunas, R., Raskinis, G.: Voice Controlled Interface for the Medical-Pharmaceutical Information System. In: Skersys, T., Butleris, R., Butkiene, R. (eds.) ICIST 2012. CCIS, vol. 319, pp. 288–296. Springer, Heidelberg (2012)
Saon, G., Chien, J.-T.: Large-Vocabulary Continuous Speech Recognition Systems: A Look at Some Recent Advances. IEEE Signal Processing Magazine 29(6), 18–33 (2012)
Tur, G., Stolcke, A.: The CALO Meeting Speech Recognition and Understanding System. In: Proc. IEEE Spoken Language Technology Workshop, pp. 69–72 (2008)
Chelba, C., Xu, P., Pereira, F., Richardson, T.: Distributed Acoustic Modeling with Back-off N-grams. In: Proc. of ICASSP 2012, pp. 4129–4132. IEEE (2012)
Kumar, N., Andreou, A.: Heteroscedastic Discriminant Analysis and Reduced Rank HMMs for Improved Speech Recognition. Speech Communication 25(4), 283–297 (1998)
Ganapathiraju, A., Hamaker, J., Picone, J.: Hybrid SVM/HMM architectures for speech recognition. In: Proc. of Interspeech, vol. 11, pp. 504–507 (2000)
Rudzionis, V., Raskinis, G., Maskeliunas, R., Rudzionis, A., Ratkevicius, K.: Comparative Analysis of Adapted Foreign Language and Native Lithuanian Speech Recognizers for Voice User Interface. Elektronika ir Elektrotechnika 19(7) (in press, 2013)
Maskeliūnas, R., Rudžionis, A., Ratkevičius, K., Rudžionis, V.: Investigation of foreign languages models for Lithuanian speech recognition. Elektronika ir Elektrotechnika 3, 15–20 (2009)
Vaičiūnas, A.: Statistical Language Models of Lithuanian and their Application to Very Large Vocabulary Continuous Speech Recognition. Summary of PhD thesis, Vytautas Magnus University, Kaunas (2006)
Young, S., Kershaw, D., Odell, J., Ollason, D., Valtchev, V., Woodland, P.: The HTK Book, Cambridge (2000)
Cohen, W.W.: Fast Effective Rule Induction. In: Proceedings of the Twelfth International Conference on Machine Learning, pp. 115–123 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rudžionis, V., Ratkevičius, K., Rudžionis, A., Raškinis, G., Maskeliunas, R. (2013). Recognition of Voice Commands Using Hybrid Approach. In: Skersys, T., Butleris, R., Butkiene, R. (eds) Information and Software Technologies. ICIST 2013. Communications in Computer and Information Science, vol 403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41947-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-41947-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41946-1
Online ISBN: 978-3-642-41947-8
eBook Packages: Computer ScienceComputer Science (R0)