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» Universal background model based speech recognition
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ICASSP
2011
IEEE
14 years 1 months ago
Acoustic model training for non-audible murmur recognition using transformed normal speech data
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Denis Babani, Tomoki Toda, Hiroshi Saruwatari, Kiy...
ICPR
2008
IEEE
15 years 11 months ago
Application of triphone clustering in acoustic modeling for continuous speech recognition in Bengali
The performance of the acoustic models is highly reflective on the overall performance of any continuous speech recognition system. Hence generation of an accurate and robust acou...
Anupam Basu, Gaurav Garg, Pabitra Mitra, Pratyush ...
TNN
2010
227views Management» more  TNN 2010»
14 years 4 months ago
Self-Organizing MultiLayer Perceptron
Abstract--A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied ...
B. Gas
ICASSP
2011
IEEE
14 years 1 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
ICAPR
2001
Springer
15 years 2 months ago
Character Extraction from Interfering Background - Analysis of Double-Sided Handwritten Archival Documents
The sipping of ink through the pages of certain double-sided handwritten documents after long periods of storage poses a serious problem to human readers or OCR systems. This pape...
Chew Lim Tan, Ruini Cao, Qian Wang, Peiyi Shen