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基于HMM的主题分类语音识别器的无监督训练

Unsupervised Training of an HMM-based Speech Recognizer for Topic Classification
课程网址: http://videolectures.net/clsp_gish_recognizer/  
主讲教师: Herb Gish
开课单位: BBN技术公司
开课时间: 2012-02-15
课程语种: 英语
中文简介:
当没有兴趣语料库的文本时,我们解决了语音主题分类的问题。我们采取的方法是一种增量学习演讲的语音语料库从自适应分割,导致代发现声单位,这些单位的节段识别器,最后一个演讲的初始标记的训练HMM语音识别器。训练的识别器是BBN的Byblos系统。我们讨论了该系统的性能,并考虑了当有少量转录数据可用时的情况。
课程简介: We address the problem of performing topic classification of speech when no transcriptions from the speech corpus of interest are available. The approach we take is one of incremental learning about the speech corpus starting with adaptive segmentation of the speech, leading to the generation of discovered acoustic units and a segmental recognizer for these units, and finally to an initial tokenization of the speech for the training of a HMM speech recognizer. The recognizer trained is BBN's Byblos system. We discuss the performance of this system and also consider the case when a small amount of transcribed data is available.
关 键 词: 语音处理; 语音识别器; 无监督训练
课程来源: 视频讲座网
最后编审: 2021-05-14:yumf
阅读次数: 58