Efficient, high-performance algorithms for N-Best search
HLT '90 Proceedings of the workshop on Speech and Natural Language
HLT '90 Proceedings of the workshop on Speech and Natural Language
The harpy speech recognition system.
The harpy speech recognition system.
The N-Best algorithm: an efficient procedure for finding top N sentence hypotheses
HLT '89 Proceedings of the workshop on Speech and Natural Language
An overview of the SPHINX-II speech recognition system
HLT '93 Proceedings of the workshop on Human Language Technology
Progressive-search algorithms for large-vocabulary speech recognition
HLT '93 Proceedings of the workshop on Human Language Technology
Progress in transcription of broadcast News using Byblos
Speech Communication
Techniques to achieve an accurate real-time large-vocabulary speech recognition system
HLT '94 Proceedings of the workshop on Human Language Technology
HLT '94 Proceedings of the workshop on Human Language Technology
Efficient backward decoding of high-order hidden Markov models
Pattern Recognition
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This paper deals with search algorithm for real-time speech recognition. We argue that software-only speech recognition has several critical advantages over using special or parallel hardware. We present a history of several advances in search algorithms, which together, have made it possible to implement real-time recognition of large vocabularies on a single workstation without the need for any hardware accelerators. We discuss the Forward-Backward Search algorithm in detail, as this is the key algorithm that has made possible recognition of very large vocabularies in real-time. The result is that we can recognize continuous speech with a vocabulary of 20,000 words strictly in real-time entirely in software on a high-end workstation with large memory. We demonstrate that the computation needed grows as the cube root of the vocabulary size.