In automatic speech recognition (ASR) systems, the speech signal is captured and
parameterized at front end and evaluated at back end using the statistical framework of …

In this paper, authors tried to develop reduced combinational features for emotional speech
recognition. The spectral/cepstral features like wavelet coefficient, LPCC (linear prediction …

A speech recognition system converts the speech-sound into the corresponding text. The
uttered speech is first understood by the machine and then the corresponding text is …

This paper implements the continuous Hindi Automatic Speech Recognition (ASR) system
using the proposed integrated features vector with Recurrent Neural Network (RNN) based …

Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

Speech recognition has become one of the most significant parts of human-computer
interaction due to emergence of new technologies such as smartphone, smart watch and …

Abstract An Automatic Speech Recognition (ASR) system implementation uses a
conventional pattern recognition technique that stores a set of training patterns in classes …

Abstract Automatic Speech Recognition (ASR) has become one of the major research areas
over the past decade and gained a lot of interest. Their system implementation, adaptation to …

The classical approach to build an automatic speech recognition (ASR) system uses
different feature extraction methods at the front end and various parameter classification …

State-of-the-art automatic speech recognition (ASR) systems follow a well established
statistical paradigm, that of parameterization of speech signals (aka feature extraction) at …