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Context-Aware Speech Interface for Human-Robot Interaction

Tülin, İzer Kaptan (2017) Context-Aware Speech Interface for Human-Robot Interaction. DLR-Interner Bericht. DLR-IB-RM-OP-2017-271. Masterarbeit. Technische Universität München.

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Kurzfassung

The focus of this thesis is the emerging field of human-robot interaction (HRI). Speech is the most intuitive way of communication between humans. This thesis aims at introducing speech recognition capabilities to RAZER, an intuitive graphical human-robot interface with an integrated framework. Additionally, the architecture of the framework is extended generically in order to support multiple interaction methods. While interaction via a graphical user interface (GUI) is effective, it may not be suitable for the cases where the user needs their hands to be free. Thus, further interaction methods are needed as an alternative or as complementary to the GUI. In the scope of this thesis, different speech recognition tools and speech recognition limitations are analyzed. A custom language model is created for speech decoding. An I/O service is implemented in order to support different interaction methods. A speech interaction concept is implemented via CMU Pocketsphinx and the custom language model created. For the evaluation of the system, a user study is conducted. The system is evaluated in terms of usefulness and efficiency. Furthermore, Google Speech API and CMU Pocketsphinx tools are compared using both generic and customized language models for Pocketsphinx by means of accuracy. The results suggest that speech interface is a useful complement to the GUI. According to accuracy tests, CMU Pocketsphinx with the customized language model is the most accurate amongst three tools. Google Speech API is the second best tool and CMU Pocketsphinx with the generic language model delivered the worst results.

elib-URL des Eintrags:https://elib.dlr.de/117405/
Dokumentart:Berichtsreihe (DLR-Interner Bericht, Masterarbeit)
Titel:Context-Aware Speech Interface for Human-Robot Interaction
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Tülin, İzer Kaptantulinizer (at) gmail.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Dezember 2017
Referierte Publikation:Nein
Open Access:Nein
Status:veröffentlicht
Stichwörter:Speech recognition, Human-Robot Interface
Institution:Technische Universität München
Abteilung:Fakultät für Informatik
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Technik für Raumfahrtsysteme
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R SY - Technik für Raumfahrtsysteme
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Intelligente Mobilität (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Robotik und Mechatronik (ab 2013) > Kognitive Robotik
Hinterlegt von: Steinmetz, Franz
Hinterlegt am:19 Dez 2017 15:01
Letzte Änderung:24 Jan 2020 11:12

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