Mobile service robots in human environments need to have versatile abilities to perceive and to interact with their environment. Spoken language is a natural way to interact with a robot, in general, and to instruct it, in particular. However, most existing speech recognition systems often suffer from high environmental noise present in the target domain and they require in-depth knowledge of the underlying theory in case of necessary adaptation to reach the desired accuracy. We propose and evaluate an architecture for a robust speaker independent speech recognition system using off-the-shelf technology and simple additional methods. We first use close speech detection to segment closed utterances which alleviates the recognition process. By further utilizing a combination of an FSG based and an N-gram based speech decoder we reduce false positive recognitions while achieving high accuracy. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Doostdar, M., Schiffer, S., & Lakemeyer, G. (2009). A robust speech recognition system for service-robotics applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5399 LNAI, pp. 1–12). https://doi.org/10.1007/978-3-642-02921-9_1
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