Abstract
A system for automatic labeling and segmentation of speech signals starting from their corresponding text will be described2. The system uses continuous Hidden Markov Models (HMM) to represent a predefined set of acoustic-phonetic units and pronunciation networks to allow different phonetic realizations of a given sentence. The system has been applied to an American (TIMIT) and an Italian (APASCI) speech database.
This work is a contribution to MAIA (Modello Avanzato di Intelligenza Artificiale, Advanced Model of Artificial Intelligence)project, which is currently under development at IRST.
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References
[1] A. Marzal and E. Vidal,“A Review and New Approaches for Automatic Segmentation of Speech Signals”, Proceedings of the European Signal Processing Conference, pp. 43–55, Barcelona, Spain. September 1990.
[2] L. F. Lamel and J. L. Gauvain, “Experiments on Speaker-Independent Phone Recognition Using BREF.”. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Vol 1, pp. 557–560, San Francisco, USA, 1992.
[3] F. Brugnara, D. Falavigna, and M. Omologo,“A HMM-Based System for Automatic Segmentation and Labeling of Speech”, Proceedings of the International Conference on Spoken and Language Processing, pp. 803–806, Banff, Alberta, Canada, October 1992.
[4] L. F. Lamel, R. H. Kassel, and S. Seneff, “Speech Database Development: Design and Analysis of the Acoustic-Phonetic Corpus”, Proceedings of the DARPA Speech Recognition Workshop, pp. 100–109, Palo Alto, California, USA, February 1986.
[5] B. Angelini, F. Brugnara, D. Falavigna, D. Giuliani, R. Gretter, M. Omologo, “A Baseline of a Speaker Independent Continuous Speech Recognizer of Italian”, Proceedings Eurospeech, Berlin, Germany, September 1993.
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© 1995 Springer-Verlag Berlin Heidelberg
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Angelini, B., Brugnara, F., Falavigna, D., Giuliani, D., Gretter, R., Omologo, M. (1995). Automatic Speech Labeling Using Word Pronunciation Networks and Hidden Markov Models. In: Ayuso, A.J.R., Soler, J.M.L. (eds) Speech Recognition and Coding. NATO ASI Series, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-57745-1_5
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DOI: https://doi.org/10.1007/978-3-642-57745-1_5
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