Abstract
We present the AMI 2006 system for the transcription of speech in meetings. The system was jointly developed by multiple sites on the basis of the 2005 system for participation in the NIST RT’05 evaluations. The paper describes major developments such as improvements in automatic segmentation, cross-domain model adaptation, inclusion of MLP based features, improvements in decoding, language modelling and vocal tract length normalisation, the use of a new decoder, and a new system architecture. This is followed by a comprehensive description of the final system and its performance in the NIST RT’06s evaluations. In comparison to the previous year word error rate results on the individual headset microphone task were reduced by 20% relative.
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Hain, T., Burget, L., Dines, J., Garau, G., Karafiat, M., Lincoln, M., McCowan, I., Moore, D., Wan, V., Ordelman, R., Renals, S.: The development of the AMI system for the transcription of speech in meetings. In: Renals, S., Bengio, S. (eds.) MLMI 2005. LNCS, vol. 3869, pp. 344–356. Springer, Heidelberg (2006)
Hain, T., Dines, J., Garau, G., Karafiat, M., Moore, D., Wan, V., Ordelman, R., Renals, S.: Transcription of conference room meetings: an investigation. In: Proc. Interspeech 2005 (2005)
Stolcke, A., Anguera, X., Boakye, K., Cetin, O., Grezl, F., Janin, A., Manda, A., Peskin, B., Wooters, C., Zheng, J.: Further progress in meeting recognition: The icsi-sri spring 2005 speech-to-text evaluation system. In: Proc. NIST RT 2005 Workshop (2005)
Hain, T., Burget, L., Dines, J., Garau, G., Karafiat, M., Lincoln, M., McCowan, I., Moore, D., Wan, V., Ordelman, R., Renals, S.: The 2005 AMI system for the transcription of speech in meetings. In: Proc. NIST RT 2005 Workshop, Edinburgh (2005)
Schwarz, P., Matìjka, P., Cernocký, J.: Towards lower error rates in phoneme recognition. In: Proc. of 7th Intl. Conf. on Text, Speech and Dialogue, p. 8. Springer, Brno (2004)
Gales, M.J.F.: Linear transformations for hmm-based speech recognition. Technical Report CUED/F-INFENG/TR-291, Cambridge University Engineering Department (1997)
Messerschmitt, D., Hedberg, D., Cole, C., Haoui, A.: P.Winship: Digital voice echo canceller with a tms32020. Application report SPRA129, Texas Instruments (1989)
Wrigley, S., Brown, G., Wan, V., Renals, S.: Speech and crosstalk detection in multichannel audio. IEEE Trans.Speech and Audio Processing 13(1), 84–91 (2005)
Zhu, Q., Chen, A.S.B., Morgan, N.: Using MLP features in sri’s conversationl speech recognition system. In: Proc. Interspeech 2005 (2005)
Povey, D.: Discriminative Training for Large Vocabulary Speech, Recognition. PhD thesis, Cambridge University (2004)
Povey, D., Gales, M.J.F., Kim, D.Y., Woodland, P.C.: MMI-MAP and MPE-MAP for acoustic model adaptation. In: Proc. Eurospeech 2003 (2003)
Bulyko, I., Ostendorf, M., Stolcke, A.: Getting more mileage from web text sources for conversational speech language modeling using class-dependent mixtures. In: Proc. Human Language Technology Conference 2003 (2003)
Wan, V., Hain, T.: Strategies for language model web-data collection. In: Proc. ICASSP 2006. Number SLP-P17.11 (2006)
Moore, D., Dines, J., Doss, M.M., Vepa, J., Cheng, O., Hain, T.: Juicer: A weighted finite state transducer speech decoder. In: Renals, S., Bengio, S., Fiscus, J.G. (eds.) MLMI 2006. LNCS, vol. 4299, pp. 285–296. Springer, Heidelberg (2006)
Mohri, M., Pereira, F., Riley, M.: General-purpose finite-state machine software tools. Technical report, AT&T Labs -Research (1997)
Hetherington, L.: The mit fst toolkit. Technical report, L. Hetherington, The MIT FST toolkit, MIT Computer Science and Artificial Intelligence Laboratory (2005) (May 2005), http://people.csail.mit.edu/ilh/fst
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Hain, T. et al. (2006). The AMI Meeting Transcription System: Progress and Performance. In: Renals, S., Bengio, S., Fiscus, J.G. (eds) Machine Learning for Multimodal Interaction. MLMI 2006. Lecture Notes in Computer Science, vol 4299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11965152_37
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DOI: https://doi.org/10.1007/11965152_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69267-6
Online ISBN: 978-3-540-69268-3
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