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» Modeling durations of syllables using neural networks
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CSL
2007
Springer
13 years 4 months ago
Modeling durations of syllables using neural networks
In this paper, we propose a neural network model for predicting the durations of syllables. A four layer feedforward neural network trained with backpropagation algorithm is used ...
K. Sreenivasa Rao, B. Yegnanarayana
ICASSP
2011
IEEE
12 years 8 months ago
Syllabification of conversational speech using Bidirectional Long-Short-Term Memory Neural Networks
Segmentation of speech signals is a crucial task in many types of speech analysis. We present a novel approach at segmentation on a syllable level, using a Bidirectional Long-Shor...
Christian Landsiedel, Jens Edlund, Florian Eyben, ...
ESANN
2007
13 years 6 months ago
A hierarchical model for syllable recognition
Inspired by recent findings on the similarities between the primary auditory and visual cortex we propose a neural network for speech recognition based on a hierarchical feedforw...
Xavier Domont, Martin Heckmann, Heiko Wersing, Fra...
TNN
1998
111views more  TNN 1998»
13 years 4 months ago
Modular recurrent neural networks for Mandarin syllable recognition
Abstract—A new modular recurrent neural network (MRNN)based speech-recognition method that can recognize the entire vocabulary of 1280 highly confusable Mandarin syllables is pro...
Sin-Horng Chen, Yuan-Fu Liao
INFORMATICALT
2008
122views more  INFORMATICALT 2008»
13 years 4 months ago
Modeling Phone Duration of Lithuanian by Classification and Regression Trees, using Very Large Speech Corpus
Classification and regression tree approach was used in this research to model phone duration of Lithuanian. 300 thousand samples of vowels and 400 thousand samples of consonants e...
Giedrius Norkevicius, Gailius Raskinis