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Speech recognition with deep recurrent neural networks论文翻译 评分:

循环神经网络在语音识别中的应用 LSTM 双向RNN 双向lstm

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【9】Speech recognition with deep recurrent neural networks.pdf

Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs for sequence labelling problems where the input-output alignment is unknown. The combination of these methods with the L

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speech recognition

这是语音识别技术的第一个例子。 语音技术的概念实际包括两个技术:合成器和识别器(参见图 1)。语音合成器将文本作为输入,并产生 音频流作为输出。语音合成也称为“文本到语音”(text-to-speech,TTS)。另一方面,语音识别器的行 探究 Windows Vista 中新的语音识别与合成 API 为刚好相反。它将音频流作为输入,并将其转换为文本副本。 对于合成器而言,将一串字符转换为听起来符合规范的音频流需要做大量工作。想象其工作方式的最简单 的方法是分析一个两部分系统的前端和后端。

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Robust Speech Recognition

Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition

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Speech Recognition Software

语音识别软件说明文档 包括SPHINX,XVIOCE等等

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Automatic Speech Recognition

ASR brief introduction

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HMM and Speech Recognition

HMM and Speech Recognition, latex presentation

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Fundamental of speech recognition

Fundamental of speech recognition是Lawrence Rabiner 和Biing-hwang Juang编写的语音识别方面的权威著作,很经典。

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speech recognition with recurrent network

speech recognition with RNNs

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Robust automatic speech recognition

系统讲解语音信号处理,已经语音识别基本原理及应用,对接cmu sphinx

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hmm based speech recognition

基于HMM的说话人语音识别,matlab编写,有测试语音数据,参考价值很大。

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c Fundamentals of Speech Recognition

Fundamentals_of_Speech_Recognition 语音识别入门必备

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Speech Recognition and Acoustic Features in

Speech Recognition and Acoustic Features in Combined Electric and Acoustic Stimulation

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