P95-1005 corpus of 20 spontaneous Spanish scheduling dialogues containing a total of 630 sentences
P95-1005 analysis of naturally occurring scheduling dialogues . Figures 1 and 2 contain examples
P95-1005 corpus of 20 spontaneous Spanish scheduling dialogues containing a total of 630 sentences
P95-1016 usually expected in an appointment scheduling dialogue . In case unexpected input occurs
P09-1101 Verbmobil-2 , a corpus of appointment scheduling dialogues . ( A description of this corpus
A00-2041 extracted from a corpus of spontaneous scheduling dialogues collected in English . For both
P95-1005 adapted from naturally occurring scheduling dialogues . These examples contain the
A97-1007 corpus of spoken and transliterated scheduling dialogues . More than 500 of them have
P97-1068 this assumption was also made for scheduling dialogues in the Verbmobil project ( Maier
P95-1016 ondemand translation of appointment scheduling dialogues . • Another use of dialogue
E97-1068 this assumption was also made for scheduling dialogues in the Verbmobil project ( Maier
A97-2003 part of efficient and cooperative scheduling dialogues . 3 The Demonstration Scenario
E95-1026 concerning a given topic . appointment scheduling dialogues The dialogue consists Of three
P98-2193 bilingual corpus of appointment scheduling dialogues . It describes a scheme to detect
E95-1026 VERBMOBIL corpus of appointment , scheduling dialogues for their occurrence and for
A97-1007 analysis . Thematic Inferences In scheduling dialogues , referring expressions like
P95-1005 outperforms Standard TST on spontaneous scheduling dialogues . In summary , Figure 6 makes
J00-3003 VERBMOBIL corpus consists of two-party scheduling dialogues . A number of the DA modeling
P98-1095 conclusion holds for our meeting scheduling dialogue data , but intuitively its applicability
C96-1024 of spoken language appointment scheduling dialogues collected for the project and
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