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This work is mainly intended at identifying emotion contribution of different vowels in Telugu language. Instead of processing the entire speech signal we propose to focus only vowel parts of the utterance (/a/, /i/, /u/, /e/ and /o/). By analysing the vowels we can discriminate the emotions. In this work spectral and prosodic features are used for studying the effect of emotions on different vowels...
The present work explores the significance of the consonant-vowel (CV) transition and steady vowel (SV) regions for language identification (LID) task. The language-specific vocal tract information represented by Mel-frequency cepstral coefficients (MFCCs), extracted from the CV transition and steady vowel regions for LID task. The duration of CV transition and steady vowel regions are varied to analyze...
In this work, source features are explored for classifying infant cries. Different types of infant cries considered in this work are hunger, pain and wet-diaper. The various excitation source features explored in this work are source features namely epoch interval contour (EIC), epoch strength contour (ESC), epoch sharpness, slope of EIC and ESC features. In this work Gaussian Mixture Models (GMM)...
In this paper we explore the performance of multilingual speaker recognition systems developed on the IITKGP-MLILSC speech corpus. Closed-set speaker identification and speaker verification experiments are individually conducted on 13 widely spoken Indian languages. In particular, we focus on the effect of language mismatch in the speaker recognition performance of individual languages and all languages...
The basic goal of this work is to develop a Consonant-Vowel Recognition System (CVRS) for determining a sequence of Consonant-Vowel (CV) units present in a given speech utterance. In this work, we are focusing on developing CVRSs for Indian languages namely Bengali and Odia. This framework of developing CVRSs can be extended to any Indian languages. We have developed two separate CVRSs for Bengali...
In this paper, spectral and prosodic features are explored for recognition of infant cry. Different types of infant cries considered in this work are wet-diaper, hunger and pain. In this work, mel-frequency cepstral coefficients (MFCC) are used to represent the spectral information, and short-time frame energies (STE) and pause duration are used for representing the prosodic information. Support Vector...
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