A Comprehensive Survey on Bengali Phoneme Recognition

TL;DR

This survey reviews various phoneme recognition methods for Bengali, focusing on Hidden Markov Models and neural networks, discussing their effectiveness and feature table construction for improved speech recognition.

Contribution

It provides a comprehensive comparison of HMM and neural network approaches, highlighting advancements in Bengali phoneme recognition techniques.

Findings

Neural networks outperform traditional HMM methods in accuracy.

Multilayer neural networks offer significant advantages over single-layer models.

Enhanced phonetic feature tables improve recognition performance.

Abstract

Hidden Markov model based various phoneme recognition methods for Bengali language is reviewed. Automatic phoneme recognition for Bengali language using multilayer neural network is reviewed. Usefulness of multilayer neural network over single layer neural network is discussed. Bangla phonetic feature table construction and enhancement for Bengali speech recognition is also discussed. Comparison among these methods is discussed.