原文:語音識別算法閱讀之EESEN

論文: EESEN:END TO END SPEECH RECOGNITION USING DEEP RNN MODELS AND WFST BASED DECODING 現狀: 混合DNN仍然GMM為其提供初始化的幀對齊,需要迭代訓練強制對齊,以及決策樹 end end的asr面臨問題: 如何將發音詞典和語言模型更好的融入解碼中 現有算法模型缺乏共享的實驗平台進行基准測試 思想: 網絡框架采用 ...

2020-09-15 23:06 0 770 推薦指數:

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語音識別算法閱讀之CTC

論文:   CTC:Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks 思想:   語音識別中,一般包含語音 ...

Sun Sep 13 23:36:00 CST 2020 0 752
語音識別算法閱讀之DFSMN

論文: Deep-FSMN for Large Vocabulary Continuous Speech Recognition 思想:   對於大詞匯量語音識別,往往需要更深的網絡結構,但是當FSMN[1]或cFSMN[2]的結構很深時容易引發剃度消失和爆炸問題 ...

Thu Sep 17 05:51:00 CST 2020 0 863
語音識別算法閱讀之LAS

LAS:   listen, attented and spell,Google 思想:   sequence to sequence的思想,模型分為encoder和dec ...

Mon Sep 14 00:00:00 CST 2020 0 883
語音識別算法閱讀之RNN-T-2018

論文:   EXPLORING ARCHITECTURES, DATA AND UNITS FOR STREAMING END-TO-END SPEECH RECOGNITION WITH RNN- ...

Wed Sep 16 06:26:00 CST 2020 0 2315
語音識別算法閱讀之LC-BLSTM優化版

論文:   IMPROVING LATENCY-CONTROLLED BLSTM ACOUSTIC MODELS FOR ONLINE SPEECH RECOGNITION 思想:   BLSTM作為當前主流的序列建模算法,在語音識別領域取得了不錯的效果。但因 ...

Wed Sep 16 18:11:00 CST 2020 0 589
 
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