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Margin-based discriminative learning of hidden Markov models for speech recognition

Margin-based discriminative learning of hidden Markov models for speech recognition
用于语音识别的隐马尔可夫模型的基于间隔的判别学习
批准号:
261540-2008
负责人:
Jiang, Hui
金额:
$2.04万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2011
资助国家:
加拿大
项目状态:
已结题
起止时间:
2011-01-01 至 2012-12-31

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中文摘要
翻译
在这个研究项目中,我们将研究用于自动语音识别的新型判别学习算法。它们被称为判别式学习,因为它们的目标是从可用的训练数据中自动学习最相关的信息,以实现识别和分类的目的。我们的研究将集中在如何定义一个好的学习标准,以及如何在学习过程中使用有效的优化方法,在大词汇量语音识别的背景下。我们希望我们的研究工作同样适用于其他模式分类任务,如文本分类,光学字符识别,生物信息学,计算机视觉等。
英文摘要
In this research program, we will study novel discriminative learning algorithms for automatic speech recognition. They are called discriminative learning because they aim to automatically learn the most relevant information from available training data for the purpose of recognition and classification. Our research will focus on how to define a good criterion for learning and how to use effective optimization methods during learning process in the context of large vocabulary speech recognition. We expect our research work will be equally applicable to other pattern classification tasks as well, such as text categorization, optical character recognition, bioinformatics, computer vision and others.
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