“Sinovoice-2014-01-13”版本间的差异

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(以内容“=Project management= * Xiaoming and Xiao Na were added into the mail list * Potential Huawei conference-transcribing project was discussed =DNN training= ==Environme...”创建新页面)
 
470 hour 8k training
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{| class="wikitable"
 
{| class="wikitable"
! CE !! MPE1!! MPE2 !! MPE3 !! MPE4
+
! Model !! CE !! MPE1!! MPE2 !! MPE3 !! MPE4
 
|-
 
|-
|23.27/22.85 || 21.35/18.87 || 21.18/18.76 || 21.07/18.54
+
|4k states||23.27/22.85 || 21.35/18.87 || 21.18/18.76 || 21.07/18.54
 
|-
 
|-
|22.16/22.22 || - ||20.36/17.94 || - ||
+
|8k states ||22.16/22.22 || - ||20.36/17.94 || - ||
 
|-
 
|-
 
|}
 
|}

2014年1月13日 (一) 05:55的版本

Project management

  • Xiaoming and Xiao Na were added into the mail list
  • Potential Huawei conference-transcribing project was discussed

DNN training

Environment setting

  • New disk space (3T) was created and mounted at /nfs/disk1
  • Jobs with 100 threads work fine on the cluster

Corpora

  • How many extra data were obtained?


470 hour 8k training

  • CE training done
  • MPE training partially done
Model CE MPE1 MPE2 MPE3 MPE4
4k states 23.27/22.85 21.35/18.87 21.18/18.76 21.07/18.54
8k states 22.16/22.22 - 20.36/17.94 -

6000 hour 16k trainin

  • Audio files done. File with incorrect sampling rates were removed
  • Lexicon and LM were done
  • Making MFCC features

DNN Decoder

  • Initial trail of DNN decoder based on the Sinovoice code was failed, largely due to FST compiler
  • Change the strategy to an integrated approach: use the sinovoice system to control connections, and use Kaldi base for asr engine