Talking to Machines: Introducing Robot Perception to Resolve Speech Recognition Uncertainties |
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Authors: | Stanislao Lauria |
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Affiliation: | (1) Department of Information Systems and Computing, Brunel University, Uxbridge UB8 3PH, United Kingdom |
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Abstract: | The use of spontaneous speech as a form of communication between humans and robots is a potential solution for more efficient
human-robot interactions. Accuracy is one of the main problems associated with the automatic speech recognition (ASR) component
of human-robot interactive systems. The standard ASR approach is
based on statistical methods applied to phoneme domains. However, some problems cannot be solved with the rule-based approaches
used so far; therefore, alternative strategies could be the solution. The aim of this paper is to investigate some aspects
related to the use of a robot's perceptive abilities to increase the robustness of ASR
components. The robot evaluative abilities are used to incrementally build knowledge that will be used during the
recognition phase. This paper covers aspects concerning the use of time-warping algorithms to improve the speech recognition
performance. In particular, aspects related to the accuracy and efficiency of this approach when applied to whole-sentence
speech signals are discussed. |
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Keywords: | |
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