2013-04-19

Data sharing

• AM/lexicon/LM are shared.
• LM count files are still in transfering.

DNN progress

400 hour DNN training

Test Set	Tencent Baseline	bMMI	fMMI	BN(with fMMI)	Hybrid
1900	8.4	7.65	7.35	6.57	7.27
2044	22.4	24.44	24.03	21.77	20.24
online1	35.6	34.66	34.33	31.44	30.53
online2	29.6	27.23	26.80	24.10	23.89
map	24.5	27.54	27.69	23.79	22.46
notepad	16	19.81	21.75	15.81	12.74
general	36	38.52	38.90	33.61	31.55
speedup	26.8	27.88	26.81	22.82	22.00

• Tencent baseline is with 700h online data+ 700h 863 data, HLDA+MPE, 88k lexicon
• Our results are with 400 hour AM, 88k LM. ML+bMMI

Tencent test result

AM: 70h training data(2 day, 15 machines, 10 threads)

LM: 88k LM

Test case: general

gmmi-bmmi: 38.7%

dnn-1: 28% 11 frame window, phone-based tree

dnn-2: 34% 9 frame window, state-based tree

GPU & CPU merge

Invesigate the possibility to merge GPU and CPU code. Try to find out an easier way. (1 week)

L-1 sparse initial training

Start to investigating.

Kaldi/HTK merge

• HTK2Kaldi: the tool with Kaldi does not work.
• Kaldi2HTK: done with implementation. Testing?

Embedded progress

• Some large performance (speed) degradation with the embedded platform(1/60).
• Planning for sparse DNN.
• QA LM training, still failed. Mengyuan need more work on this.