International Journal of Parallel Programming
Fast acoustic computations using graphics processors
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
OpenMP-based parallel implementation of a continuous speech recognizer on a multi-core system
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Robust speaker segmentation for meetings: the ICSI-SRI spring 2005 diarization system
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Proceedings of the 40th Annual International Symposium on Computer Architecture
Scalable multimedia content analysis on parallel platforms using python
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Automatic speech recognition enables a wide range of current and emerging applications such as automatic transcription, multimedia content analysis, and natural human-computer interfaces. This article provides a glimpse of the opportunities and challenges that parallelism provides for automatic speech recognition and related application research from the point of view of speech researchers. The increasing parallelism in computing platforms opens three major possibilities for speech recognition systems: improving recognition accuracy in non-ideal, everyday noisy environments; increasing recognition throughput in batch processing of speech data; and reducing recognition latency in real-time usage scenarios. We describe technical challenges, approaches we've taken, and possible directions for future research to guide the design of efficient parallel software and hardware infrastructures.