Research on Segment Acoustic Model Based Mandarin LVCSR

SM has shown a better performance than HMM in connected word recognition system; however, no reports we have read show that SM has been applied in LVCSR as decoding acoustic model because of the restriction of its complexity. We have preliminarily built a SM based mandarin LVCSR system which adopts CART and global tying to tie the parameters in the triphone models and the fast SM algorithm, CF algorithm and two-level pruning to enhance the speed of decoding. The system achieves 87.09% syllable accuracy in Test-863 data corpus within 4 real times. We believe SM offers an alternative choice for LVCSR system though further research for its fast algorithms by rational utilization of its structure information.

• Type: Conference
• Year: 2009
• Where: ISNN
• Authors: Wenju Liu, Yun Tang, Shouye Peng
• Keywords: Artificial Intelligence, Connected Word Recognition, Fast Sm Algorithm, ISNN 2009, SM Based Mandarin