Fundamentals of speech recognition
Fundamentals of speech recognition
Towards efficiency and portability: programming with the BSP model
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
Finite-state transducers in language and speech processing
Computational Linguistics
Scalable HMM based inference engine in large vocabulary continuous speech recognition
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Parallelization and analysis of speech recognition on mobile multi-core processor
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Opportunities and challenges of parallelizing speech recognition
HotPar'10 Proceedings of the 2nd USENIX conference on Hot topics in parallelism
Proceedings of the 2010 international workshop on Searching spontaneous conversational speech
| Hi-index | 0.00 |
Computer speech recognition has been very successful in limited domains and for isolated word recognition. However, widespread use of large-vocabulary continuous-speech recognizers is limited by the speed of current recognizers, which cannot reach acceptable error rates while running in real time. This paper shows how to harness shared memory multiprocessors, which are becoming increasingly common, to increase the speed significantly, and therefore the accuracy or vocabulary size, of a speech recognizer. To cover the necessary background, we begin with a tutorial on speech recognition. We then describe the parallelization of an existing high-quality speech recognizer, achieving a speedup of a factor of 3, 5, and 6 on 4-, 8-, and 12-processors respectively for the benchmark North American business news (NAB) recognition task.