equipes:rcln:ancien_wiki:projets:parsing_enhancing_conversationnal_service_robot

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equipes:rcln:ancien_wiki:projets:parsing_enhancing_conversationnal_service_robot [2019/04/09 12:07]
rosse [2017]
equipes:rcln:ancien_wiki:projets:parsing_enhancing_conversationnal_service_robot [2020/11/23 18:41] (Version actuelle)
garciaflores ↷ Page déplacée de equipes:rcln:projets:parsing_enhancing_conversationnal_service_robot à equipes:rcln:ancien_wiki:projets:parsing_enhancing_conversationnal_service_robot
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 +====== Parsing enhancing of the conversational module for a service robot ======
 +
 ===== Abstract ===== ===== Abstract =====
 The goal of the project is to improve the syntactic parser of the Golem service robot[(Meza Ruiz I.V., Rascón C., Pineda Cortes L.A. (2013) [[http://link.springer.com/content/pdf/10.1007%2F978-3-642-45111-9_37.pdf|Practical Speech Recognition for Contextualized Service Robots]]. In: Castro F., Gelbukh A., González M. (eds) Advances in Soft Computing and Its Applications. MICAI 2013. Lecture Notes in Computer Science, vol 8266. Springer, Berlin, Heidelberg)][([[https://www.google.com.mx/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwiN49-iv_fTAhUIqlQKHc9KBUYQFggqMAA&url=http%3A%2F%2Fwww.robocup2016.org%2Fmedia%2Fsymposium%2FTeam-Description-Papers%2FAtHome%2FRoboCup_2016_AtHome_TDP_golem.pdf&usg=AFQjCNHm5_1RldjKLeGqB-sLgXV6FdYfEw&sig2=2JWWID7uIBZFKR-Lgcgnfg|The Golem Team, RoboCup@Home 2016]])]. The parsing module takes its imput from the Automatic Speech Recognition (ASR), which produces a text line to be parsed. The output of the parser is a SitLog command which triggers an action in the robot. The goal of the project is to improve the syntactic parser of the Golem service robot[(Meza Ruiz I.V., Rascón C., Pineda Cortes L.A. (2013) [[http://link.springer.com/content/pdf/10.1007%2F978-3-642-45111-9_37.pdf|Practical Speech Recognition for Contextualized Service Robots]]. In: Castro F., Gelbukh A., González M. (eds) Advances in Soft Computing and Its Applications. MICAI 2013. Lecture Notes in Computer Science, vol 8266. Springer, Berlin, Heidelberg)][([[https://www.google.com.mx/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwiN49-iv_fTAhUIqlQKHc9KBUYQFggqMAA&url=http%3A%2F%2Fwww.robocup2016.org%2Fmedia%2Fsymposium%2FTeam-Description-Papers%2FAtHome%2FRoboCup_2016_AtHome_TDP_golem.pdf&usg=AFQjCNHm5_1RldjKLeGqB-sLgXV6FdYfEw&sig2=2JWWID7uIBZFKR-Lgcgnfg|The Golem Team, RoboCup@Home 2016]])]. The parsing module takes its imput from the Automatic Speech Recognition (ASR), which produces a text line to be parsed. The output of the parser is a SitLog command which triggers an action in the robot.
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 ==== 2018 ==== ==== 2018 ====
-  -  Transform the DGC-based (Definite Clause Grammar) parser into a CCG (Combinatorial Categorial Grammar)<ref>R. Cantrell, M. Scheutz, P. Schermerhorn and X. Wu, "[[https://www.google.com.mx/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0ahUKEwiDm9Shu_fTAhXEs1QKHfAQD4AQFggzMAE&url=https%3A%2F%2Fpdfs.semanticscholar.org%2F428f%2Fcad8ea088d14cc292d2e17d151dd7b7a088e.pdf&usg=AFQjCNHXZSrCbItkGZ37utw6wvkG6I2DEQ&sig2=293KRGnAJj8D1pXwbztdEg|Robust spoken instruction understanding for HRI]]," 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Osaka, 2010, pp. 275-282.</ref><ref>M. Eppe, S. Trott and J. Feldman, "[[https://arxiv.org/pdf/1604.06721|Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction]]," 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, 2016, pp. 731-738.</ref> based parser +  -  Transform the DGC-based (Definite Clause Grammar) parser into a CCG (Combinatorial Categorial Grammar)[(R. Cantrell, M. Scheutz, P. Schermerhorn and X. Wu, "[[https://www.google.com.mx/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0ahUKEwiDm9Shu_fTAhXEs1QKHfAQD4AQFggzMAE&url=https%3A%2F%2Fpdfs.semanticscholar.org%2F428f%2Fcad8ea088d14cc292d2e17d151dd7b7a088e.pdf&usg=AFQjCNHXZSrCbItkGZ37utw6wvkG6I2DEQ&sig2=293KRGnAJj8D1pXwbztdEg|Robust spoken instruction understanding for HRI]]," 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Osaka, 2010, pp. 275-282.)][(M. Eppe, S. Trott and J. Feldman, "[[https://arxiv.org/pdf/1604.06721|Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction]]," 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, 2016, pp. 731-738.)] based parser 
-  -  Evaluate Google's Parsey MacParseface<ref>[[https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html +  -  Evaluate Google's Parsey MacParseface[([[https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html 
-Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source]]</ref> with the service robot oriented parsing evaluation testbed.+Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source]])] with the service robot oriented parsing evaluation testbed.
  
 ==== 2019 ==== ==== 2019 ====
  • Dernière modification: il y a 5 ans