Abstract
The relationship between speech and language processing is an important problem to be solved in order to achieve continuous large-vocabulary speech recognition for a speech translation system or the human interface of a man-machine system. For the recognition of large-vocabulary continuous speech, first the phonemes are recognized by HMM (Hidden Markov Model). A generalized LR parser is introduced to predict next words/phonemes. The Japanese utterance is successfully recognized by the combined HMM-LR parser (HMM-LR). Many phrase candidates are filtered out of the speech recognition system through the use of linguistic information. An experimental system which translates spoken Japanese into English (SL-TRANS) has been implemented. The translation method consists of analysis, transfer and generation processes.A new method incorporated in the system analyzes the expressions of linguistic intention meanings in utterances. In applying this translation method to a goal-oriented dialogue corpus, involving inquiries and explanations regarding an international conference, the experimental system shows advantages for translating Japanese dialogues into English.
Published Version
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