A Survey on Automatic Question-answering process in Speech using Spoken term detection

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-49 Number-5
Year of Publication : 2017
Authors : M.Mamatha, T.Bhaskar Reddy


M.Mamatha, T.Bhaskar Reddy "A Survey on Automatic Question-answering process in Speech using Spoken term detection". International Journal of Computer Trends and Technology (IJCTT) V49(5):263-265, July 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The advent of WWW has reintroduced the need for user-friendly querying techniques in speech that reduce information overflow, and poses new challenges to the research in automated QA. The goal of current works of the unity of research of Technologies is to improve efficiency of e-learning by introducing intelligence into e-learning environments and automating a set of its features. The system allows learners to post subject related questions / doubts to the subject experts in speech. This usually requires the subject expert to answer the same query with different sentence framing a number of times. This paper discusses the development of an automated frequently asked questions retrieval system techniques in speech. This paper discuss few simple Speech Recognition and retrieval techniques using STD briefly.

[1] Baghai-Ravary, L., Kochanski, G., & Coleman, J. (2009). Data-driven approaches to objective evaluation of phoneme alignment sys-tems. In Proceedings of the 4th conference on human language technology , Poznan, Poland.
[2] Anupam Mandal K.R. Prasanna Kumar Pabitra Mitra “ Recent developments in spoken term detection: a survey” Springer Science+Business Media New York 2013.
[3] Barnwal, S., Sahni, K., Singh, R., & Raj, B. (2012). Spectrographic seam patterns for discriminative word spotting. InProc. int. conf.acoustics, speech and signal processing , Kyoto, Japan.
[4] M.Mamtha, D.Kavitha,T.Swathi „A Survey on automatic Question-Answering Techniques‟ in IJRCM for publication in Volume No.3(2013),Issue No.10(October).
[5] Bridle, J. (1973). An efficient elastic template method for detecting given key words in running speech. In Proc. of British acoustic society meeting, UK.
[6] Can, D. (2011). Lattice indexing for spoken term detection. IEEE Transactions on Audio, Speech, and Language Processing.
[7] Can, P., Cooper, E., Sethy, A., White, C., Ramabhadran, B., & Saraclar,M. (2009). Effect of pronunciations on oov queries in spoken term detection. In Proc. int. conf. acoustics, speech and signal process-ing , Taipei, Taiwan.
[8] Chan, C., & Lee, L. (2010). Unsupervised spoken-term detection with spoken queries using segment-based dynamic time warping. In Proc. int. conf. speech processing.

Speech Recognition, Spoken Term Detection(STD,LVCSR, HMM.