Abstract
The paper describes our system devised for recognizing speech in meetings, which was an entry in the NIST Spring 2004 Meeting Recognition Evaluation. This system was developed as a collaborative effort between ICSI, SRI, and UW and was based on SRI’s 5xRT Conversational Telephone Speech (CTS) recognizer. The CTS system was adapted to the Meetings domain by adapting the CTS acoustic and language models to the Meeting domain, adding noise reduction and delay-sum array processing for far-field recognition, and adding postprocessing for cross-talk suppression for close-talking microphones. A modified MAP adaptation procedure was developed to make best use of discriminatively trained (MMIE) prior models. These meeting-specific changes yielded an overall 9% and 22% relative improvement as compared to the original CTS system, and 16% and 29% relative improvement as compared to our 2002 Meeting Evaluation system, for the individual-headset and multiple-distant microphones conditions, respectively.
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Adami, A., Burget, L., Dupont, S., Garudadri, H., Grezl, F., Hermansky, H., Jain, P., Kajarekar, S., Morgan, N., Sivadas, S.: Qualcomm-ICSI-OGI features for ASR. In: ICSLP (2002)
Bulyko, I., Ostendorf, M., Stolcke, A.: Getting More Mileage from Web Text Sources for Conversational Speech Language Modeling using Class-Dependent Mixtures. In: HLT 2003, pp. 7–9 (2003)
Graciarena, M., Franco, H., Zheng, J., Vergyri, D., Stolcke, A.: Voicing Feature Integration in SRI’s Decipher LVCSR System. In: ICASSP 2004, Montreal (2004) (to appear)
Janin, A., Baron, D., Edwards, J., Ellis, D., Gelbart, D., Morgan, N., Peskin, B., Pfau, T., Shriberg, E., Stolcke, A., Wooters, C.: The ICSI Meeting Corpus. In: ICASSP 2003, Hong Kong (2003)
Jin, H., Matsoukas, S., Schwartz, R., Kubala, F.: Fast Robust Inverse Transform SAT and Multi-stage Adaptation. In: Proc. DARPA Broadcast News Transcription and Understanding Workshop, Lansdowne, VA, pp. 105–109 (1998)
Kumar, N.: Investigation of Silicon-Auditory Models and Generalisation of Linear Discriminant Analysis for Improved Speech Recognition. PhD thesis, John Hopkins University (1997)
Morgan, N., Baron, D., Bhagat, S., Carvey, H., Dhillon, R., Edwards, J., Gelbart, D., Janin, A., Krupski, A., Peskin, B., Pfau, T., Shriberg, E., Stolcke, A., Wooters, C.: Meetings about Meetings: Research at ICSI on Speech in Multiparty Conversations. In: ICASSP 2003, Hong Kong (2003)
Neumeyer, L., Weintraub, M.: Probabilistic Optimum Filtering for Robust Speech Recognition. In: Proc. ICASSP, Adelaide, Australia, pp. I417–I420 (1994)
Povey, D., Woodland, P.C.: Large-scale MMIE Training for Conversational Telephone Speech Recongition. In: Proc. NIST Speech Transcription Workshop, College Park, MD (2000)
Saon, G., Padmanabhan, M., Gopinath, R., Chen, S.: Maximum Likelihood Discriminant Feature Spaces. In: ICASSP 2000, pp. 1747–1750 (2000)
Vergyri, D., Stolcke, A., Gadde, V.R.R., Ferrer, L., Shriberg, E.: Prosodic Knowledge Sources for Automatic Speech Recognition. In: ICASSP 2003, Hong Kong, pp. 208–211 (2003)
Waibel, A., Bett, M., Metze, F., Reis, K., Schaaf, T., Schultz, T., Soltau, H., Yu, H., Zechner, K.: Advances in Automatic Meeting Record Creation and Access. In: ICASSP (2001)
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Wooters, C. et al. (2005). The 2004 ICSI-SRI-UW Meeting Recognition System. In: Bengio, S., Bourlard, H. (eds) Machine Learning for Multimodal Interaction. MLMI 2004. Lecture Notes in Computer Science, vol 3361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30568-2_17
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DOI: https://doi.org/10.1007/978-3-540-30568-2_17
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