Improved Hybrid Model of HMM/GMM for Speech Recognition

In this paper, we propose a speech recognition engine using hybrid model of Hidden Markov Model (HMM) and Gaussian Mixture Model (GMM). Both the models have been trained independently and the respective likelihood values have been considered jointly and input to a decision logic which provides net likelihood as the output. This hybrid model has been compared with the HMM model. Training and testing has been done by using a database of 20 Hindi words spoken by 80 different speakers. Recognition rates achieved by normal HMM are 83.5% and it gets increased to 85% by using the hybrid approach of HMM and GMM.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

Verbal Dialogue versus Written Dialogue

Modern technology has moved on and completely changed the way that people can use the telephone or mobile to dialogue with information held on computers. Well developed ���written speech analysis��� does not work with ���verbal speech���. The main purpose of our article is, firstly, to highlights the problems and, secondly, to shows the possible ways to solve these problems.

Common Scientific Lexicon for Automatic Discourse Analysis of Scientific and Technical Texts

The paper reports on preliminary results of an ongoing research aiming at development of an automatic procedure for recognition of discourse-compositional structure of scientific and technical texts, which is required in many NLP applications. The procedure exploits as discourse markers various domain-independent words and expressions that are specific for scientific and technical texts and organize scientific discourse. The paper discusses features of scientific discourse and common scientific lexicon comprising such words and expressions. Methodological issues of development of a computer dictionary for common scientific lexicon are concerned; basic principles of its organization are described as well. Main steps of the discourse-analyzing procedure based on the dictionary and surface syntactical analysis are pointed out.

Automatic ECG Analysis for Preliminary and Detailed Diagnostics Based on Scale-space Representation

A novel approach of automatic ECG analysis based on scale-scale signal representation is proposed. The approach uses curvature scale-space representation to locate main ECG waveform limits and peaks and may be used to correct results of other ECG analysis techniques or independently. Moreover dynamic matching of ECG CSS representations provides robust preliminary recognition of ECG abnormalities which has been proven by experimental results.