The NECTEC 2015 Thai Open-Domain Automatic Speech Recognition System

摘要

We describe the recent development of the NECTEC Thai open-domain automatic speech recognition system. Some of the techniques that were found beneficial over its baseline system are: hybrid word-subword language modeling to enhance the vocabulary coverage in a constraint resource; multi-conditioned noisy acoustic modeling to improve the system robustness using a newly developed large social media speech database; recent state-of-the-art speech features; and lastly, online decoding and speech compression to reduce the processing and data transmission time. These techniques result in a 32.4% word error rate on open-domain noisy speech test sets which is 35.7% relatively lower than the baseline system. The overall system operates in an average 1.2xRT which is promising for real applications.