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» Large vocabulary continuous speech recognition with context-...
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NAACL
2010
13 years 5 months ago
Contextual Information Improves OOV Detection in Speech
Out-of-vocabulary (OOV) words represent an important source of error in large vocabulary continuous speech recognition (LVCSR) systems. These words cause recognition failures, whi...
Carolina Parada, Mark Dredze, Denis Filimonov, Fre...
ICASSP
2010
IEEE
13 years 7 months ago
Speech modeling based on committee-based active learning
We propose a committee-based active learning method for large vocabulary continuous speech recognition. In this approach, multiple recognizers are prepared beforehand, and the rec...
Yuzu Hamanaka, Koichi Shinoda, Sadaoki Furui, Tada...
ICASSP
2011
IEEE
12 years 11 months ago
Using morpheme and syllable based sub-words for polish LVCSR
Polish is a synthetic language with a high morpheme-perword ratio. It makes use of a high degree of inflection leading to high out-of-vocabulary (OOV) rates, and high Language Mo...
M. Ali Basha Shaik, Amr El-Desoky Mousa, Ralf Schl...
EMNLP
2008
13 years 9 months ago
Integrating Multi-level Linguistic Knowledge with a Unified Framework for Mandarin Speech Recognition
To improve the Mandarin large vocabulary continuous speech recognition (LVCSR), a unified framework based approach is introduced to exploit multi-level linguistic knowledge. In th...
Xinhao Wang, Jiazhong Nie, Dingsheng Luo, Xihong W...
ICASSP
2011
IEEE
12 years 11 months ago
Relevance language modeling for speech recognition
Language models for speech recognition tend to be brittle across domains, since their performance is vulnerable to changes in the genre or topic of the text on which they are trai...
Kuan-Yu Chen, Berlin Chen