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» Type-2 Fuzzy Hidden Markov Models to Phoneme Recognition
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INFORMATICALT
2007
106views more  INFORMATICALT 2007»
13 years 7 months ago
Framework for Choosing a Set of Syllables and Phonemes for Lithuanian Speech Recognition
This paper describes a framework for making up a set of syllables and phonemes that subsequently is used in the creation of acoustic models for continuous speech recognition of Lit...
Sigita Laurinciukaite, Antanas Lipeika
ICASSP
2010
IEEE
13 years 7 months ago
Recognition of phonemes and words in singing
This paper studies the influence of n-gram language models in the recognition of sung phonemes and words. We train uni-, bi-, and trigram language models for phonemes and bi- and...
Annamaria Mesaros, Tuomas Virtanen
WCE
2007
13 years 8 months ago
Speech Recognition Model for Tamil Stops
—In this paper, a novel approach for implementing Tamil isolated speech phoneme recognition is described. While most of the literature on Automatic Speech Recognition (ASR) is ba...
Arumugam Rathinavelu, Anupriya Rajkumar, A. S. Mut...
PR
2010
147views more  PR 2010»
13 years 6 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
ACL
2008
13 years 9 months ago
Unsupervised Learning of Acoustic Sub-word Units
Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
Balakrishnan Varadarajan, Sanjeev Khudanpur, Emman...