Parsing enhancing of the conversational module for a service robot

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Abstract

The goal of the project is to improve the syntactic parser of the Golem robot. 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.

Work plan

2017

  1. Develop an evaluation testbed for the parser based on (Doostdar et al., 20907)[1].
  2. Train a machine learning model to generate DGC[2]

2018

2018

  1. Create an evaluation testbed for the

Participants

Références

  1. Doostdar M., Schiffer S., Lakemeyer G. (2009) A Robust Speech Regognition System for Service-Robots Application. In: Iocchi L., Matsubara H., Weitzenfeld A., Zhou C. (eds) RoboCup 2008: Robot Soccer World Cup XII. RoboCup 2008. Lecture Notes in Computer Science, vol 5399. Springer, Berlin, Heidelberg
  2. Tarau, P. and Figa, E.: Knowledge Based Conversational Agents and Virtual Storytelling. In Proceedings of the 2004 ACM Symposium on Applied Computing (Nicosia, Cyprus, March 14 - 17, 004). SAC '04. ACM Press, New York, NY, 39-44. (2004)