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Automatic identification of different voice qualities present in a speech signal which is very beneficiary for detecting any kind of speech by an efficient speech recognition system. Proposed technique is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the proposed algorithm is evaluated using the data collected from three different speakers and an overall accuracy of 87.2 % is achieved.

Produktbeschreibung
Automatic identification of different voice qualities present in a speech signal which is very beneficiary for detecting any kind of speech by an efficient speech recognition system. Proposed technique is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the proposed algorithm is evaluated using the data collected from three different speakers and an overall accuracy of 87.2 % is achieved.
Autorenporträt
La Dra. Poonam Sharma trabaja como Profesora Asociada en el Departamento de Biotecnología de la Universidad Jaypee de Tecnología de la Información, Solan. El Dr. Vikrant Abbot trabaja como profesor asociado en la Facultad de Farmacia de la Universidad Suresh Gyan Vihar, Jaipur. La Sra. Palak Sharma ha completado su proyecto de investigación de licenciatura de JUIT, Waknaghat, Solan.