Decoding with sub-word network models for out-of-vocabulary words recognition

摘要

This paper proposes a novel decoder, which cope with sub-word models effectively. Sub-word models are devised for recognition of out-of-vocabulary words. Former implementation, which handles sub-word models as registered words, enlarges language model and consumes lots of computational resources. We proposed a structured decoding method, which applies sub-word network models The proposed method makes it possible to search efficiently. Comparing between former implementation and proposed one, the proposed method achieves 90% reduction in language model size, and 50% reduction in CPU time without any deterioration of performance.