Abstract
This paper presents the ATVS-CSLT-HCTLab spoken term detection (STD) system submitted to the NIST 2013 Open Keyword Search evaluation. The evaluation consists of searching a list of query terms in Vietnamese conversational speech data. Our submission involves an automatic speech recognition (ASR) subsystem which converts speech signals into word/phone lattices, and an STD subsystem which indexes and searches for query terms. The submission is a hybrid approach which employs a word-based system to search for in-vocabulary (INV) terms and a phone-based system to search for out-of-vocabulary (OOV) terms. A term-dependent discriminative confidence estimation is employed to score confidence of detections. Although the ASR performance is not state-of-the-art, our submission achieves a moderate STD performance in the evaluation.
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References
Abad, A., Rodríguez-Fuentes, L.J., Peñagarikano, M., Varona, A., Bordel, G.: On the calibration and fusion of heterogeneous spoken term detection systems. In: Proc. of Interspeech, pp. 20–24 (2013)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: An update. SIGKDD Explorations 11(1) (2009)
Katsurada, K., Miura, S., Seng, K., Iribe, Y., Nitta, T.: Acceleration of spoken term detection using a suffix array by assigning optimal threshold values to subkeywords. In: Proc. of Interspeech, pp. 11–14 (2013)
Li, H., Han, J., Zheng, T., Zheng, G.: A novel confidence measure based on context consistency for spoken term detection. In: Proc. of Interspeech, pp. 2429–2430 (2012)
Liu, C., Wang, D., Tejedor, J.: N-gram FST indexing for spoken term detection. In: Proc. of Interspeech, pp. 2093–2096 (2012)
Martin, A., Doddington, G., Kamm, T., Ordowski, M., Przybocki, M.: The DET curve in assessment of detection task performance. In: Proc. of Eurospeech, pp. 1895–1898 (1997)
NIST: The spoken term detection (STD) 2006 evaluation plan, 10 edn. National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA (September 2006), http://www.nist.gov/speech/tests/std
Norouzian, A., Rose, R.: An approach for efficient open vocabulary spoken term detection. Speech Communication 57, 50–62 (2014)
Povey, D., Ghoshal, A., Boulianne, G., Burget, L., Glembek, O., Goel, N., Hannemann, M., Motlicek, P., Qian, Y., Schwarz, P., Silovsky, J., Stemmer, G., Vesely, K.: The KALDI speech recognition toolkit. In: Proc. of ASRU (2011)
Stolcke, A.: SRILM - an extensible language modeling tool. In: Proc. of ICSLP, pp. 901–904 (2002)
Szoke, I.: Hybrid word-subword spoken term detection. Ph.D. thesis, Brno University of Technology (June 2010)
Wang, D.: Out-of-vocabulary Spoken Term Detection. Ph.D. thesis, University of Edinburgh (December 2009)
Wang, D., King, S.: Letter-to-sound pronunciation prediction using conditional random fields. IEEE Signal Processing Letters 18(2), 122–125 (2011)
Wang, D., Tejedor, J., King, S., Frankel, J.: Term-dependent confidence normalization for out-of-vocabulary spoken term detection. Journal of Computer Science and Technology 27(2), 358–375 (2012)
Wessel, F., Macherey, K., Schluter, R.: Using word probabilities as confidence measures. In: Proc. of ICASSP, pp. 225–228 (1998)
Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X., Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V., Woodland, P.: The HTK v3.4 Book. Engineering Department, Cambridge University (March 2006)
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Tejedor, J., Toledano, D.T., Wang, D. (2014). ATVS-CSLT-HCTLab System for NIST 2013 Open Keyword Search Evaluation. In: Navarro Mesa, J.L., et al. Advances in Speech and Language Technologies for Iberian Languages. Lecture Notes in Computer Science(), vol 8854. Springer, Cham. https://doi.org/10.1007/978-3-319-13623-3_26
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DOI: https://doi.org/10.1007/978-3-319-13623-3_26
Publisher Name: Springer, Cham
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