Speech Recognition Using Matrix Comparison

Speech Emotion Recognition Using Scalogram Based Deep Structure

Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...

Speech recognition using EMG; mime speech recognition

The cellular phone offers significant benefits but causes several social problems. One such problem is phone use in places where people should not speak, such as trains and libraries. A communication style that would not require voiced speech has the potential to solve this problem. Speech recognition based on electromyography (EMG), which we call "Mime Speech Recognition" is proposed. It not o...

Environment normalization for robust speech recognition using direct cepstral comparison

In this paper we describe and evaluate a series of new algorithms that compensate for the effects of unknown acoustical environments (or changes in environment) through the use of compensation vectors that are added to the cepstral representations of speech that is input to a speech recognition system. These compensation vectors are obtained from direct frame-by-frame comparisons of the cepstra...

Structured Precision Matrix Modelling for Speech Recognition

Speech Recognition Using Dsp

This paper deals with the process of automatically recognizing who is speaking on the basis of individual information included in speech waves. Speaker recognition methods can be divided into text-independent and textdependent methods. In a textindependent system, speaker models capture characteristics of somebody's speech, which show up irrespective of what one is saying. In a text-dependent s...