2014-01-17

AM development

Sparse DNN

• Optimal Brain Damage(OBD).

1. Online OBD held.
2. OBD + L1 norm start to investigation.

• Efficient computing

1. Conducting rearrangement the matrix structure and compose zero blocks by some smart approaches, leading to better computing speed.

Efficient DNN training

1. Asymmetric window: Great improvement on training set(WER 34% to 24%), however the improvement is lost on test. Overfitting?
2. Fbank feature used to train GMM+DNN, leads to very high training Acc, but reduces accuracy on test.

Optimal phoneset

• Ch/En training with concatenated phone set is completed.
• Initial test seems reasonable on Chinese. A bit worse than the original test
• Need to compare the two systems both on Fbank
• Need to extend the state number

Engine optimization

• Investigating LOUDS FST. On progress.

LM development

NN LM

• Training character-based NN LM, 12134 Chinese chars
• Prepare data for training word2vector on Gigawords CHS 4.0

Embedded development

• CLG embedded decoder is almost done. The graph compilation is highly fast.
• Work on layer-by-layer DNN training, initial model is incorrect.

Speech QA

• Use N-best to expand match in QA. Better performance were obtained.

• 1-best matches 96/121
• 10-best matches 102/121

• Use N-best to recover errors in entity check.

• Design a non-entity pattern to discover the possible place of an entity
• By this position range, search entities within the N-best result

• Use Pinyin to recover errors in entity check. Future work.

• Design a non-entity pattern to discover the possible place of an entity (as above)
• Match the Pinying strings of all the entities, and then match the pinyin strings with the entity pinyin
• Keep the most matched entity based on Pinyin with a threshold
• A bit worse then the original test.
• A possible problem is that the LM is over-strong, thus lead to unmatched Pinyin string in acoustic space
• Liu rong will provide a weak LM to support the research.

• Investigate some errors in entity-based LM.

• Still some errors exist
• Running entity-base LM with a small entity list