Corpus ID: 1686008

Minimal training based semantic categorization in a voice activated question answering (VAQA) system

@inproceedings{Balakrishna2008MinimalTB,
  title={Minimal training based semantic categorization in a voice activated question answering (VAQA) system},
  author={Mithun Balakrishna and M. Tatu and D. Moldovan},
  booktitle={INTERSPEECH},
  year={2008}
}
In this paper, we develop a knowledge based methodology that maps Automatic Speech Recognizer (ASR) transcriptions to predefined semantic categories in a Voice Activated Question Answering (VAQA) system. The proposed semantic categorization methodology, SemCat, uses a novel lexical chains/ontology based algorithm and relies heavily on customized but domain independent Natural Language Processing (NLP) tools and does not require any domain-specific utterance collections or manually annotated… Expand

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