Abstract
We describe the development of the ICSI-SRI speech recognition system for the National Institute of Standards and Technology (NIST) Spring 2006 Meeting Rich Transcription (RT-06S) evaluation, highlighting improvements made since last year, including improvements to the delay-and-sum algorithm, the nearfield segmenter, language models, posterior-based features, HMM adaptation methods, and adapting to a small amount of new lecture data. Results are reported on RT-05S and RT-06S meeting data. Compared to the RT-05S conference system, we achieved an overall improvement of 4% relative in the MDM and SDM conditions, and 11% relative in the IHM condition. On lecture data, we achieved an overall improvement of 8% relative in the SDM condition, 12% on MDM, 14% on ADM, and 15% on IHM.
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Janin, A. et al. (2006). The ICSI-SRI Spring 2006 Meeting Recognition System. 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_39
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DOI: https://doi.org/10.1007/11965152_39
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