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Study of deep learning and CMU sphinx in automatic speech recognition

机译:深度学习和CMU狮身人面像在自动语音识别中的研究

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Machine learning has proven to be a very effective tool in automatic speech recognition. This paper is an attempt to give a broad overview of the applications of various approaches of machine learning in speech recognition with special reference to deep learning and CMU Sphinx. Deep learning in Speech recognition is a relatively recent development. On the other hand, CMU Sphinx, an open source software has been in use for this purpose for a relatively longer time. CNN, a Deep Learning algorithm learns the invariant features that help it to differentiate between different words and word sequences. CMU Sphinx uses GMM-HMM model to predict the phonemes in the utterance to determine the word or set of continuous words that were spoken.
机译:事实证明,机器学习是自动语音识别中非常有效的工具。本文旨在对各种机器学习方法在语音识别中的应用进行广泛概述,并特别参考深度学习和CMU Sphinx。语音识别中的深度学习是一个相对较新的发展。另一方面,用于此目的的开源软件CMU Sphinx使用了相对较长的时间。 CNN是一种深度学习算法,它学习不变特征,以帮助区分不同的单词和单词序列。 CMU Sphinx使用GMM-HMM模型来预测发声中的音素,以确定所讲的单词或一组连续单词。

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