| other,11-5-P03-1031,ak | this <term> ambiguity </term> based on <term> | statistical information | </term> obtained from <term> dialogue corpora | #4229 This paper proposes a method for resolving this ambiguity based onstatistical information obtained from dialogue corpora. | |
| other,12-2-P03-1031,ak | user utterances </term> based on the <term> | context | </term> of a <term> dialogue </term> . Since | #4151 This process enables the system to understand user utterances based on thecontext of a dialogue. | |
| other,17-3-P03-1031,ak | <term> user utterance </term> due to the <term> | ambiguity | </term> of <term> speech understanding </term> | #4173 Since multiple candidates for the understanding result can be obtained for a user utterance due to theambiguity of speech understanding, it is not appropriate to decide on a single understanding result after each user utterance. | |
| other,13-4-P03-1031,ak | resolving the <term> ambiguity </term> as the <term> | dialogue | </term> progresses , the <term> discourse understanding | #4207 By holding multiple candidates for understanding results and resolving the ambiguity as thedialogue progresses, the discourse understanding accuracy can be improved. | |
| tech,6-7-P03-1031,ak | Experiment results have shown that a <term> | system | </term> that exploits the proposed method | #4262 Experiment results have shown that asystem that exploits the proposed method performs sufficiently and that holding multiple candidates for understanding results is effective. | |
| tech,4-2-P03-1031,ak | systems </term> . This process enables the <term> | system | </term> to understand <term> user utterances | #4143 This process enables thesystem to understand user utterances based on the context of a dialogue. |
