WordNet: a lexical database for English
Communications of the ACM
Statistical methods for speech recognition
Statistical methods for speech recognition
High performance question/answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Corrections to "A Cache-Based Language Model for Speech Recognition"
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploiting syntactic structure for language modeling
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Experiments with open-domain textual Question Answering
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
The role of lexico-semantic feedback in open-domain textual question-answering
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Multilingual stochastic n-gram class language models
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Spoken interactive ODQA system: SPIQA
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Improving Speech Recognition and Understanding using Error-Corrective Reranking
ACM Transactions on Asian Language Information Processing (TALIP)
Language modelization and categorization for voice-activated QA
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Sibyl, a factoid question-answering system for spoken documents
ACM Transactions on Information Systems (TOIS)
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Voice-Activated Question Answering (VAQA) systems represent the next generation capability for universal access by integrating state-of-the-art in question answering Q&A and automatic speech recognition (ASR) in such a way that the performance of the combined system is better than the individual components. This paper presents an implemented VAQA system and describes the techniques that enable the terative refinement of both Q&A and ASR. The results of our experiments show that spoken questions can be processed with surprising accuracy when using our VAQA implementation.