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Advances in transcription of broadcast news and conversational telephone speech within the combined EARS BBN/LIMSI system

机译:EARS BBN / LIMSI组合系统中广播新闻和对话电话语音的转录进展

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This paper describes the progress made in the transcription of broadcast news (BN) and conversational telephone speech (CTS) within the combined BBN/LIMSI system from May 2002 to September 2004. During that period, BBN and LIMSI collaborated in an effort to produce significant reductions in the word error rate (WER), as directed by the aggressive goals of the Effective, Affordable, Reusable, Speech-to-text [Defense Advanced Research Projects Agency (DARPA) EARS] program. The paper focuses on general modeling techniques that led to recognition accuracy improvements, as well as engineering approaches that enabled efficient use of large amounts of training data and fast decoding architectures. Special attention is given on efforts to integrate components of the BBN and LIMSI systems, discussing the tradeoff between speed and accuracy for various system combination strategies. Results on the EARS progress test sets show that the combined BBN/LIMSI system achieved relative reductions of 47% and 51% on the BN and CTS domains, respectively.
机译:本文介绍了2002年5月至2004年9月在BBN / LIMSI组合系统中广播新闻(BN)和对话电话语音(CTS)转录方面的进展。在此期间,BBN和LIMSI进行了合作,以期按照有效,价格合理,可重复使用,语音转文本[国防高级研究计划局(DARPA)EARS]计划的积极目标,降低字词错误率(WER)。本文重点介绍可提高识别精度的通用建模技术,以及可有效利用大量训练数据和快速解码架构的工程方法。对集成BBN和LIMSI系统的组件的工作给予了特别的关注,讨论了各种系统组合策略在速度和准确性之间的权衡。 EARS进度测试集上的结果表明,组合的BBN / LIMSI系统在BN和CTS域上分别实现了47%和51%的相对减少。

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