In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language proc...In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.展开更多
In recent years, there have been emergent interests in L2 learners＇ implicit lexical knowledge. Researchers employed psycholinguistic methods to investigate the online processing of formulaic sequences in L2 （idioms...In recent years, there have been emergent interests in L2 learners＇ implicit lexical knowledge. Researchers employed psycholinguistic methods to investigate the online processing of formulaic sequences in L2 （idioms and collocations） and find evidence for holistic processing of the target linguistic sequences. This paper reviews and comments on lexical bundles and related concepts, trying to make clear this well focused research area in second language acquisition （SLA）. Literature is reviewed and criticized on frequency effect in L2 learning, formulaic sequences, and implicit/explicit knowledge/learning, including their theoretical basis, methodology, and conclusion. In this paper, the author argues that sufficient practice, either receptive or productive, can turn explicit knowledge implicit, making it automatically accessed and retrieved. Suggestions on further study in lexical bundles are given.展开更多
基金Project(60763001)supported by the National Natural Science Foundation of ChinaProjects(2009GZS0027,2010GZS0072)supported by the Natural Science Foundation of Jiangxi Province,China
文摘In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.
文摘In recent years, there have been emergent interests in L2 learners＇ implicit lexical knowledge. Researchers employed psycholinguistic methods to investigate the online processing of formulaic sequences in L2 （idioms and collocations） and find evidence for holistic processing of the target linguistic sequences. This paper reviews and comments on lexical bundles and related concepts, trying to make clear this well focused research area in second language acquisition （SLA）. Literature is reviewed and criticized on frequency effect in L2 learning, formulaic sequences, and implicit/explicit knowledge/learning, including their theoretical basis, methodology, and conclusion. In this paper, the author argues that sufficient practice, either receptive or productive, can turn explicit knowledge implicit, making it automatically accessed and retrieved. Suggestions on further study in lexical bundles are given.
