1. Mengyuan Zhao CSLT, RIIT, Tsinghua University 2016-01-06
Summary of 2015
Mengyuan Zhao
CSLT, RIIT, Tsinghua University

2. Contents Research Project Other DAE/CDAE
Speaker adapted ASR / Language vector in ASR
Dark knowledge
Project
Bi-lingual AM
Tag-LM
Phone number / Car number recognition
LSTM AM (based on nnet1)
Parallel AM training (based on nnet3)
Other
Server purchase/maintain

3. Research

4. Research
DAE/CDAE
Paper published. (APSIPA 2015 best paper award)

5. Research Speaker adapted ASR Language vector in ASR Dark knowledge
WER 6.42%  6.11% (Aurora4)
Language vector in ASR
WER CN 20.83%  20.26%
WER EN 57.50%  47.17%
Dark knowledge
Knowledge transfer become standard process in AM training (20% improvement in car number recognition);

6. Project

7. Project Bi-lingual AM Tag-lm Chinese, OK; English, OK;
Chinese + few English words, OK;
Tag-lm
Deal with new words out of LM word list, for example, actor names, movie names.

8. Project Phone number / Car number recognition Phone number recognition
SER < 10%
Car number recognition
SER 50%  20% (better than Baidu)

9. Project LSTM AM (based on nnet1) LSTM has strong learning ability;
LSTM perform so good with small LM;
LSTM is easy to diverge and over-fitting;
Not so good with big LM;
Training is so slow (7×slower than DNN).

10. Project Parallel AM training (based on nnet3)
Speed up 4-5 times (with 8 GPUs);
Lots of investigations and experiments
Network type (DNN, TDNN, LSTM, CTC);
Activation function (RELU, sigmoid, P-norm);
Network structure (TDNN, 7*2048, RELU);
Big-lm decoder;
Discriminative training (MPE);
Best model WER:
16k: 9.04%  8.45%;
8k: 14.61%  12.66%

11. Other

12. Other Purchase / Install Maintain Computer: 2 servers, 3 PCs;
GPU: 2*GTX970;
Hard disk: /work3;
n*cpu fans;
Maintain
Psychology lecture.

13. Thanks