The recognition method of user’s feedback during the system’s utterance is proposed and its application to the spoken dialogue system is discussed. In human conversation, we can know the dialogue partner’s internal state by receiving such feedbacks. Our research topics are (1) developing the prosodic informa-tion based feedback recognizer and (2) appropriately control-ling the system’s utterance timing along with the user’s feed-backs. The implemented recognizer can distinguish between back-channel and ask-back word-independently with prosodic information based features and statistical recognition method. Experiments of the spoken dialogue system with this function reveals when it should generate the next utterance after receiv-ing the user...
Back-channel feedback is required in order to build spoken dialog systems that are responsive. This ...
Spoken dialogue systems provide a convenient way for users to interact with a machine using only spe...
Kopp S, Stocksmeier T, Gibbon D. Incremental Multimodal Feedback for Conversational Agents. In: Pela...
If a dialog system were to respond to a user as naturally as a human, interaction would be smoother....
Traditional dialogue systems use a fixed silence threshold to detect the end of users ’ turns. Such ...
A conversation robot which can generate a back-channel feedback appropriately to the user is develop...
A spoken dialogue system of information retrieval on academic documents has been developed with a sp...
The domain of the speech recognition and dialog system EVAR is train time table inquiry. We observed...
In this chapter, we present a system that provides real-time feedback about an ongoing discussion. V...
Parallel with the orthographic streams of words in conversation are multiple layered epiphenomena, s...
If a dialog system could respond to a user as naturally as a human, the interaction would be smoothe...
Abstract. Participation in natural, real-time dialogue calls for behaviors sup-ported by perception-...
Abstract. Just like humans, conversational computer systems should not listen silently to their inpu...
The domain of the speech recognition and dialog system EVAR is train time table inquiry. We observed...
Feedback utterances such as 'yeah', 'mhm', and 'okay', convey different communicative functions depe...
Back-channel feedback is required in order to build spoken dialog systems that are responsive. This ...
Spoken dialogue systems provide a convenient way for users to interact with a machine using only spe...
Kopp S, Stocksmeier T, Gibbon D. Incremental Multimodal Feedback for Conversational Agents. In: Pela...
If a dialog system were to respond to a user as naturally as a human, interaction would be smoother....
Traditional dialogue systems use a fixed silence threshold to detect the end of users ’ turns. Such ...
A conversation robot which can generate a back-channel feedback appropriately to the user is develop...
A spoken dialogue system of information retrieval on academic documents has been developed with a sp...
The domain of the speech recognition and dialog system EVAR is train time table inquiry. We observed...
In this chapter, we present a system that provides real-time feedback about an ongoing discussion. V...
Parallel with the orthographic streams of words in conversation are multiple layered epiphenomena, s...
If a dialog system could respond to a user as naturally as a human, the interaction would be smoothe...
Abstract. Participation in natural, real-time dialogue calls for behaviors sup-ported by perception-...
Abstract. Just like humans, conversational computer systems should not listen silently to their inpu...
The domain of the speech recognition and dialog system EVAR is train time table inquiry. We observed...
Feedback utterances such as 'yeah', 'mhm', and 'okay', convey different communicative functions depe...
Back-channel feedback is required in order to build spoken dialog systems that are responsive. This ...
Spoken dialogue systems provide a convenient way for users to interact with a machine using only spe...
Kopp S, Stocksmeier T, Gibbon D. Incremental Multimodal Feedback for Conversational Agents. In: Pela...