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- W2106033504 abstract "This paper introduces our work on mandarin lecture speech transcription. In particular, we present our work on a small database, which contains only 16 hours of audio data and 0.16 M words of text data. A range of experiments have been done to improve the performances of the acoustic model and the language model, these include adapting the lecture speech data to the reading speech data for acoustic modeling and the use of lecture conference paper, power points and similar domain web data for language modeling. We also study the effects of automatic segmentation, unsupervised acoustic model adaptation and language model adaptation in our recognition system. By using a 3timesRT multiple passes decoding strategy, we obtain 70.3% accuracy performance in our final system. Finally, we apply our speech transcription system into a SVM summarizer and obtain a ROUGE-L F-measure of 66.5%." @default.
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- W2106033504 date "2007-01-01" @default.
- W2106033504 modified "2023-09-27" @default.
- W2106033504 title "A Mandarin lecture speech transcription system for speech summarization" @default.
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- W2106033504 doi "https://doi.org/10.1109/asru.2007.4430157" @default.
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