“140603 Mengyuan Zhao”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
(以内容“Weekly report: *gamma-tone-filter bank (GTFBANK) test on Tencent data. results on cvss. *Sinovoice EN training: xEnt & MPE training ,done.test them on cmu-lm and giga-l...”创建新页面)
 
 
第2行: 第2行:
 
*gamma-tone-filter bank (GTFBANK) test on Tencent data. results on cvss.
 
*gamma-tone-filter bank (GTFBANK) test on Tencent data. results on cvss.
 
*Sinovoice EN training:
 
*Sinovoice EN training:
xEnt & MPE training ,done.test them on cmu-lm and giga-lm.
+
#xEnt & MPE training ,done.test them on cmu-lm and giga-lm.
 
*Sinovoice multi-language training based on 1400h_Dianhua + 100h_Shujutang (8K)
 
*Sinovoice multi-language training based on 1400h_Dianhua + 100h_Shujutang (8K)
 
#Fbank, xEnt 16 iters done.
 
#Fbank, xEnt 16 iters done.
 
#Start GTFBANK_stream training. xEnt 9 iters done.
 
#Start GTFBANK_stream training. xEnt 9 iters done.
 
*Test frame-skipping decode method on Tencent fbank model. result shows that WER have a little increament (<1%).
 
*Test frame-skipping decode method on Tencent fbank model. result shows that WER have a little increament (<1%).

2014年6月3日 (二) 04:47的最后版本

Weekly report:

  • gamma-tone-filter bank (GTFBANK) test on Tencent data. results on cvss.
  • Sinovoice EN training:
  1. xEnt & MPE training ,done.test them on cmu-lm and giga-lm.
  • Sinovoice multi-language training based on 1400h_Dianhua + 100h_Shujutang (8K)
  1. Fbank, xEnt 16 iters done.
  2. Start GTFBANK_stream training. xEnt 9 iters done.
  • Test frame-skipping decode method on Tencent fbank model. result shows that WER have a little increament (<1%).