Efficient Embedded Speech Recognition for Very Large Vocabulary Mandarin Car-Navigation Systems

Automatic speech recognition (ASR) for a very large vocabulary of isolated words is a difficult task on a resource-limited embedded device. This paper presents a novel fast decoding algorithm for a Mandarin speech recognition system which can simultaneously process hundreds of thousands of items and maintain high recognition accuracy. The proposed algorithm constructs a semi-tree search network based on Mandarin pronunciation rules, to avoid duplicate syllable matching and save redundant memory. Based on a two-stage fixed-width beam-search baseline system, the algorithm employs a variable beam-width pruning strategy and a frame-synchronous word-level pruning strategy to significantly reduce recognition time. This algorithm is aimed at an in-car navigation system in China and simulated on a standard PC workstation. The experimental results show that the proposed method reduces recognition time by nearly 6-fold and memory size nearly 2- fold compared to the baseline system, and causes less than 1% accuracy degradation for a 200,000 word recognition task

Analysis of Influencing Factors of Knowledge Sharing in the Virtual Academic Community: Based on the Motivation and Demand Theory

Virtual academic community is an important position for academic exchange activities of contemporary academic users, while knowledge sharing and communication are the key to its survival and development, as well as its core value. Based on the influence of the characteristics of the virtual academic community on the content of knowledge sharing, the paper integrated the motivation and demand theory, and established the influencing factor model of knowledge sharing in the virtual academic community. The results show that pleasure in helping people, trust and social connections have the significant positive influence on knowledge sharing behavior, Trust and social connections have the significant positive influence on knowledge sharing quality of members in virtual academic community, and reputation and reciprocity have little influence on knowledge sharing quality