Natural language parsing as statistical pattern recognition
Natural language parsing as statistical pattern recognition
A maximum entropy approach to natural language processing
Computational Linguistics
Trainable methods for surface natural language generation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Phrase splicing and variable substitution using the IBM trainable speech synthesis system
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
High-quality speech-to-speech translation for computer-aided language learning
ACM Transactions on Speech and Language Processing (TSLP)
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This paper presents a statistical speech-to-speech machine translation (MT) system for limited domain applications using a cascaded approach. This architecture allows for the creation of multilingual applications. In this paper, the system architecture and its components, including the speech recognition, parsing, information extraction, translation, natural language generation (NLG) and text-to-speech (TTS) components are described. We have implemented the described system for translating speech between Mandarin and English language pair in an air travel application domain. We are current porting the system to the military domain. Encouraging experimental results have been observed and are presented.