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ICASSP
2009
IEEE
15 years 4 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...
CSL
2004
Springer
14 years 9 months ago
Factor analysed hidden Markov models for speech recognition
Recently various techniques to improve the correlation model of feature vector elements in speech recognition systems have been proposed. Such techniques include semi-tied covaria...
Antti-Veikko I. Rosti, M. J. F. Gales
69
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AUSAI
2004
Springer
15 years 2 months 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»
15 years 3 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
INTERSPEECH
2010
14 years 4 months ago
Hidden Markov models with context-sensitive observations for grapheme-to-phoneme conversion
Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...