Publications (7)0 Total impact
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Conference Proceeding: Phone Segmentation for Japanese Triphthong Using Neural Networks
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ABSTRACT: Context information influences the performance of Automatic Speech Recognition (ASR). Current Hidden Markov Model (HMM) based ASR systems have solved this problem by using context-sensitive tri-phone models. However, these models need a large number of speech parameters and a large volume of speech corpus. In this paper, we propose a technique to model a dynamic process of co-articulation and embed it to ASR systems. Recurrent Neural Network (RNN) is expected to realize this dynamic process. But main problem is the slowness of RNN for training the network of large size. We introduce Distinctive Phonetic Feature (DPF) based feature extraction using a two-stage system consists of a Multi-Layer Neural Network (MLN) in the first stage and another MLN in the second stage where the first MLN is expected to reduce the dynamics of acoustic feature pattern and the second MLN to suppress the fluctuation caused by DPF context. The experiments are carried out using Japanese triphthong data. The proposed DPF based feature extractor provides better segmentation performance with a reduced mixture-set of HMMs. Better context effect is achieved with less computation using MLN instead of RNN.Information Technology: New Generations (ITNG), 2011 Eighth International Conference on; 05/2011 -
Conference Proceeding: Development of Analysis Rules for Bangla Part of Speech for Universal Networking Language
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ABSTRACT: The Universal Networking Language (UNL) is a worldwide generalizes form human interactive in machine independent digital platform for defining, recapitulating, amending, storing and dissipating knowledge or information among people of different affiliations. The theoretical and practical research associated with these interdisciplinary endeavor facilities in a number of practical applications in most domains of human activities such as creating globalization trends of market or geopolitical independence among nations. In our research work we have tried to develop analysis rules for Bangla part of speech which will help to create a doorway for converting the Bangla language to UNL and vice versa and overcome the barrier between Bangla to other Languages.Information Technology: New Generations (ITNG), 2011 Eighth International Conference on; 05/2011 -
Conference Proceeding: Bangla phoneme recognition for different acoustic features
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ABSTRACT: In this paper, we compare among performance of different acoustic features for Bangla Automatic Speech Recognition (ASR). Most of the Bangla ASR system uses a small number of speakers, but 40 speakers selected from a wide area of Bangladesh, where Bangla is used as a native language, are involved here. In the experiments, mel-frequency cepstral coefficients (MFCCs) and local features (LFs) are inputted to the hidden Markov model (HMM) based classifiers for obtaining phoneme recognition performance. It is shown from the experimental results that MFCC-based method of 39 dimensions provides a higher phoneme correct rate and accuracy than the other methods investigated.Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on; 01/2011 -
Conference Proceeding: Effect of articulatory $Delta$ and $Delta$$Delta$ parameters on multilayer neural network based speech recognition
Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on; 01/2010 -
Conference Proceeding: Bangla speech recognition using two stage multilayer neural networks
Signal and Image Processing (ICSIP), 2010 International Conference on; 01/2010 -
Conference Proceeding: Bangla triphone HMM based word recognition
Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on; 01/2010 -
Conference Proceeding: Articulatory $Delta$ and $Delta$$Delta$ parameters effect on HMM-based classifier for ASR
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on; 01/2010
