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» Continuous speech recognition with a TF-IDF acoustic model
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ICASSP
2009
IEEE
14 years 2 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
AUSAI
2004
Springer
14 years 24 days ago
Reliable Unseen Model Prediction for Vocabulary-Independent Speech Recognition
Speech recognition technique is expected to make a great impact on many user interface areas such as toys, mobile phones, PDAs, and home appliances. Those applications basically re...
Sungtak Kim, Hoirin Kim
ISCAS
2006
IEEE
162views Hardware» more  ISCAS 2006»
14 years 1 months ago
Silicon neurons that phase-lock
Abstract—We present a silicon neuron with a dynamic, active leak that enables precise spike-timing with respect to a time-varying input signal. Our neuron models the mammalian bu...
J. H. Wittig Jr., Kwabena Boahen
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
ICASSP
2011
IEEE
12 years 11 months ago
Towards robust word discovery by self-similarity matrix comparison
Word discovery is the task of discovering and collecting occurrences of repeating words in the absence of prior acoustic and linguistic knowledge, or training material. The capabi...
Armando Muscariello, Guillaume Gravier, Fré...