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ICASSP
2008
IEEE
13 years 11 months ago
Exploiting contextual information for improved phoneme recognition
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Cont...
Joel Pinto, B. Yegnanarayana, Hynek Hermansky, Mat...
INTERSPEECH
2010
12 years 11 months ago
Automatic speech recognition system channel modeling
In this paper, we present a systems approach for channel modeling of an Automatic Speech Recognition (ASR) system. This can have implications in improving speech recognition compo...
Qun Feng Tan, Kartik Audhkhasi, Panayiotis G. Geor...
AIRS
2004
Springer
13 years 10 months ago
Improving Transliteration with Precise Alignment of Phoneme Chunks and Using Contextual Features
Abstract. Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM’s conventional MT mo...
Wei Gao, Kam-Fai Wong, Wai Lam
LREC
2008
174views Education» more  LREC 2008»
13 years 6 months ago
Automatic Phoneme Segmentation with Relaxed Textual Constraints
Speech synthesis by unit selection requires the segmentation of a large single speaker high quality recording. Automatic speech recognition techniques, e.g. Hidden Markov Models (...
Pierre Lanchantin, Andrew C. Morris, Xavier Rodet,...
TSD
2010
Springer
13 years 2 months ago
Hybrid HMM/BLSTM-RNN for Robust Speech Recognition
The question how to integrate information from different sources in speech decoding is still only partially solved (layered architecture versus integrated search). We investigate t...
Yang Sun, Louis ten Bosch, Lou Boves