Speech interaction strategies for a humanoid assistant
The goal of SecondHands, a H2020 project, is to design a robot that can offer help to a maintenance technician in a proactive manner. The robot is to act as a second pair of hands that can assist the technician when he is in need of help. In order for the robot to be of real help to the technician,...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201816101002 |
| _version_ | 1818622715854061568 |
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| author | Stüker Sebastian Constantin Stefan Niehues Jan Nguyen Thai-Son Müller Markus Pham Ngoc Quan Rüde Robin Waibel Alex |
| author_facet | Stüker Sebastian Constantin Stefan Niehues Jan Nguyen Thai-Son Müller Markus Pham Ngoc Quan Rüde Robin Waibel Alex |
| author_sort | Stüker Sebastian |
| collection | DOAJ |
| description | The goal of SecondHands, a H2020 project, is to design a robot that can offer help to a maintenance technician in a proactive manner. The robot is to act as a second pair of hands that can assist the technician when he is in need of help. In order for the robot to be of real help to the technician, it needs to understand his needs and follow his commands. Interaction via speech is a crucial part of this. Due to the nature of the situation in which the interactions take place, often the technician needs to speak to the robot when under stress performing strenuous physical labor, the classical turn based interaction schemes need to be transformed into dialogue systems that perform stream processing, anticipating user intentions, correcting itself as more information become available, in order to be able to respond in a rapid manner. In order to meet these demands, we are developing low-latency streaming based automatic speech recognition systems in combination with recurrent neural network based Natural Language Understanding systems that perform slot filling and intent recognition in order for the robot to provide assistance in a rapid manner, that can be partly based on speculative classifications that are then being refined as more speech becomes available. |
| first_indexed | 2024-12-16T18:29:35Z |
| format | Article |
| id | doaj.art-096486f5803a4581866d552705e2da48 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-16T18:29:35Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-096486f5803a4581866d552705e2da482022-12-21T22:21:19ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011610100210.1051/matecconf/201816101002matecconf_erzr2018_01002Speech interaction strategies for a humanoid assistantStüker SebastianConstantin StefanNiehues JanNguyen Thai-SonMüller MarkusPham Ngoc QuanRüde RobinWaibel AlexThe goal of SecondHands, a H2020 project, is to design a robot that can offer help to a maintenance technician in a proactive manner. The robot is to act as a second pair of hands that can assist the technician when he is in need of help. In order for the robot to be of real help to the technician, it needs to understand his needs and follow his commands. Interaction via speech is a crucial part of this. Due to the nature of the situation in which the interactions take place, often the technician needs to speak to the robot when under stress performing strenuous physical labor, the classical turn based interaction schemes need to be transformed into dialogue systems that perform stream processing, anticipating user intentions, correcting itself as more information become available, in order to be able to respond in a rapid manner. In order to meet these demands, we are developing low-latency streaming based automatic speech recognition systems in combination with recurrent neural network based Natural Language Understanding systems that perform slot filling and intent recognition in order for the robot to provide assistance in a rapid manner, that can be partly based on speculative classifications that are then being refined as more speech becomes available.https://doi.org/10.1051/matecconf/201816101002 |
| spellingShingle | Stüker Sebastian Constantin Stefan Niehues Jan Nguyen Thai-Son Müller Markus Pham Ngoc Quan Rüde Robin Waibel Alex Speech interaction strategies for a humanoid assistant MATEC Web of Conferences |
| title | Speech interaction strategies for a humanoid assistant |
| title_full | Speech interaction strategies for a humanoid assistant |
| title_fullStr | Speech interaction strategies for a humanoid assistant |
| title_full_unstemmed | Speech interaction strategies for a humanoid assistant |
| title_short | Speech interaction strategies for a humanoid assistant |
| title_sort | speech interaction strategies for a humanoid assistant |
| url | https://doi.org/10.1051/matecconf/201816101002 |
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