DNN-HMM based Automatic Speech Recognition for HRI Scenarios

In this paper, we propose to replace the classical black box integration of automatic speech recognition technology in HRI applications with the incorporation of the HRI environment representation and modeling, and the robot and user states and contexts. Accordingly, this paper focuses on the enviro...

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Veröffentlicht in:	2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI) S. 150 - 159
Hauptverfasser:	Novoa, José, Wuth, Jorge, Escudero, Juan Pablo, Fredes, Josué, Mahu, Rodrigo, Yoma, Néstor Becerra
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	New York, NY, USA ACM 26.02.2018
Schriftenreihe:	ACM Conferences
Schlagworte:	Acoustics Computing methodologies > Artificial intelligence > Natural language processing Computing methodologies > Artificial intelligence > Natural language processing > Speech recognition DNN-HMM Error analysis Hardware > Robustness > Fault tolerance > Redundancy Human-centered computing > Interaction design > Interaction design process and methods Human-centered computing > Interaction design > Interaction design process and methods > Contextual design Human-centered computing > Interaction design > Interaction design process and methods > Scenario-based design Loudspeakers Robot sensing systems speech recognition time-varying acoustic channel Training Training data speech recognition dnn-hmm time-varying acoustic channel
ISBN:	9781450349536, 1450349536
ISSN:	2167-2148
Online-Zugang:	Volltext
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