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Rule-based recognition of phoneme classes
2nd International Conference on Spoken Language Processing (ICSLP 1992), 1992Item does not contain ...
Ederveen, D.N.M., Boves, L.W.J.
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Word Recognition in a Phonemic Dyslexic Patient
Quarterly Journal of Experimental Psychology, 1975The systems underlying word recognition were investigated in a single case study of a patient (K.F.) with an acquired dyslexia. His reading performance was related to parts of speech, word frequency and word concreteness, and his reading errors were analysed.
Shallice, Timothy, WARRINGTON EK
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Fuzzy Sets and Systems, 1988
First, a scheme for pattern recognition is given. In a learning step, a relation between acoustic characteristics and the corresponding phoneme is computed using an inference rule. Next, the phonemes are recognized as result of a fuzzy relation equation.
Lamotte, Michel +2 more
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First, a scheme for pattern recognition is given. In a learning step, a relation between acoustic characteristics and the corresponding phoneme is computed using an inference rule. Next, the phonemes are recognized as result of a fuzzy relation equation.
Lamotte, Michel +2 more
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Phoneme Grouping for Speech Recognition
The Journal of the Acoustical Society of America, 1967A program for associating a given segment of speech with a phoneme group, such as a vowellike segment, fricativelike segment, etc., is described. Some disadvantages of the presently accepted grouping of phonemes into stops, fricatives, vowels, etc., are discussed.
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The Journal of the Acoustical Society of America, 1992
The possibility of phoneme recognition using a hardware-based spectral sampling filter and a 386-μ processor software-based neural network to accurately recognize ten spoken vowel sounds of the English language was explored. To apply the neural network to speech recognition, a set of inputs conducive to the neural network architecture must be supplied.
James Lisonbee, Dan Tebbs, Paul Wheeler
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The possibility of phoneme recognition using a hardware-based spectral sampling filter and a 386-μ processor software-based neural network to accurately recognize ten spoken vowel sounds of the English language was explored. To apply the neural network to speech recognition, a set of inputs conducive to the neural network architecture must be supplied.
James Lisonbee, Dan Tebbs, Paul Wheeler
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Phoneme recognition in contiunous speech using phoneme discriminant filters
ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005We describe in this paper a new phoneme recognition system using phoneme discriminant filters for speaker independent continuous speech. The segmentation of speech and the classification of phoneme are carried out simultaneously by the phoneme discriminant filters.
Satoshi Moriai +2 more
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A new approach to phoneme recognition by phoneme filter neural networks
Information Sciences, 1996This paper describes a phoneme filter neural network (PFN) approach to phoneme recognition. Most conventional speech recognition neural networks have a serious drawback: the network output values do not correspond to candidate likelihoods. The PFN is a multilayer neural network with fewer hidden units than input units prepared for each of the phoneme ...
Masami Nakamura +2 more
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Phoneme-by-phoneme recognition of speech composed of the words of given vocabulary
ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005Initial word reference signals are built from the finite set of the reference elements and written by means of acoustic-phonetic transcription. The transformations of the initial word references permitting to obtain reference signals of words with the different rate of pronunciation are introduced.
Taras K. Vintsiuk +2 more
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A phoneme effect in visual word recognition
Cognition, 1998In alphabetic writing systems like English or French, many words are composed of more letters than phonemes (e.g. BEACH is composed of five letters and three phonemes, i.e./biJ/). This is due to the presence of higher order graphemes, that is, groups of letters that map into a single phoneme (e.g. EA and CH in BEACH map into the single phonemes /i/ and
Rey, Arnaud +3 more
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Sparse Multilayer Perceptron for Phoneme Recognition
IEEE Transactions on Audio, Speech, and Language Processing, 2012This paper introduces the sparse multilayer perceptron (SMLP) which jointly learns a sparse feature representation and nonlinear classifier boundaries to optimally discriminate multiple output classes. SMLP learns the transformation from the inputs to the targets as in multilayer perceptron (MLP) while the outputs of one of the internal hidden layers ...
Garimella S. V. S. Sivaram +1 more
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