深度学习在语音识别中的研究进展综述

摘要

在当今的大数据时代里,对于处理大量未经标注的原始语音数据的传统机器学习算法,很多都已不再适用.与此同时,深度学习模型凭借其对海量数据的强大建模能力,能够直接对未标注数据进行处理,成为当前语音识别领域的一个研究热点.主要分析和总结了当前几种具有代表性的深度学习模型,介绍了其在语音识别中对于语音特征提取及声学建模中的应用,最后总结了当前所面临的问题和发展方向.%In the era of big data, many of traditional machine learning methods of disposing unlabeled raw voice data have become less applicable.At the same time, deep learning models can directly process unlabeled data because of its powerful capability of modeling to deal with the massive data, and has become a hot research in the field of speech recognition.To begin with, this paper analyzed and summarized the state-of-the-art deep learning of models.And then,it discussed the applications to speech recognition with speech features extraction and acoustic modeling.Finally,it concluded the problems faced and development orientation.