Abstract
We introduce new method for discriminating speech and non-speech segments in audio signals based on the transcriptions produced by phoneme recognizers. Four measures based on consonant-vowels and voiced-unvoiced pairs obtained from different phonemes speech recognizers were proposed. They were constructed in a way to be recognizer and language independent and could be applied in different segmentation-classification frameworks. The segmentation systems were evaluated on different broadcast news datasets consisted of more than 60 hours of multilingual BN shows. The results of these evaluations illustrate the robustness of the proposed features in comparison to MFCC and posterior probability based features. The overall frame accuracies of the proposed approaches varied in range from 95% to 98% and remained stable through different test conditions and different phoneme recognizers.
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References
Ajmera, J., McCowan, I., Bourlard, H.: Speech/music segmentation using entropy and dynamism features in HMM classification framework. Speech Communication 40(3), 351–363 (2003)
Graff, D.: An overview of Broadcast News corpora. Speech Comm. – special issue on Broadcast News Processsing 37(1), 15–26 (2002)
Garofolo, J.S., Lamel, L.F., Fisher, W.M., Fiscus, J.G., Pallett, D.S., Dahlgren, N.L.: DARPA TIMIT acoustic-phonetic continuous speech corpus. U.S. Dept. of Commerce. NIST, Gaithersburg, MD (1993)
Magrin-Chagnolleau, I., Parlangeau-Vallès, N.: Audio indexing: what has been accomplished and the road ahead. In: Proceedings of Joint Conference on Information Sciences (JCIS 2002), Durham, North Carolina, pp. 911–914 (2002)
Mihelič, F., et al.: Spoken language resources at LUKS of the University of Ljubljana. International Journal of Speech Technology 6(3), 221–232 (2003)
Picone, J.W.: Signal modeling techniques in speech recognition. Proceedings of the IEEE 81(9), 1215–1247 (1993)
Reynolds, D.A., et al.: Beyond Cepstra: Exploiting High-Level Information in Speaker Recognition. In: Proceedings of the Workshop on Multimodal User Authentication, Santa Barbara, California, pp. 223–229 (2003)
Reynolds, D.A., Torres-Carrasquillo, P.A.: Approaches and Applications of Audio Diarization. In: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), Philadelphia, USA (2005)
Shafran, I., Rose, R.: Robust speech detection and segmentation for real-time ASR applications. In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), Hong Kong, pp. 432–435 (2003)
Siegler, M., Jain, U., Raj, B., Stern, R.: Automatic Segmentation, Classification and Clustering of Broadcast News Data. In: Proceedings of the DARPA Speech Recognition Workshop, Chantilly, VA, USA, pp. 97–99 (1997)
Williams, G., Ellis, D.P.W.: Speech/music discrimination based on posterior probabilities. In: Proceedings of ES 1999, Budapest, Hungary, vol. 2, pp. 687–690 (1999)
Žibert, J., Mihelič, F.: Development of Slovenian Broadcast News Speech Database. In: Proceedings of the International Conference on Language Resources and Evaluation (LREC 2004), Lisbon, Portugal, pp. 2095–2098 (2004)
Žibert, J., et al.: The COST278 Broadcast News Segmentation and Speaker Clustering Evaluation - Overview, Methodology, Systems, Results. In: Proceedings of Interspeech 2005, Lisbon, Portugal, pp. 629–632 (2005)
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Mihelič, F., Žibert, J. (2006). Robust Speech Detection Based on Phoneme Recognition Features. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_57
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DOI: https://doi.org/10.1007/11846406_57
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