Zhiyuan Tang 2015-12-14
来自cslt Wiki
Last week:
1. launched experiments on 1400h-Chinese plus 100h English with CTC/nnet3/Kaldi, it's much faster than those on train97 as it's on train88 with 8 jobs parallel;
2. got refered ruselts of Kaldi/CTC on 1400h-Chinese[1];
3. turned to SPEAKER.
This week:
1. more research about SPEAKER;
2. supervise the experiments;
3. reading.
TASKS
End-to-End
- monophone ASR --Zhiyuan
- MPE
- CTC/nnet3/Kaldi
conditioning learning
- language vector into multiple layers --Zhiyuan
- a Chinese paper
- speech rate into multiple layers --Zhiyuan
- verify the code for extra input(s) into DNN