Title: New features for language recognition from speech signal

Authors: M. Sadanandam; V. Kamaskhiprasad

Addresses: Kakatiya University, Warangal, Telangana, India ' JNTU-Hyderabad, Telangana, India

Abstract: In this paper, we derive new feature vectors for identifying the language from short utterance of speech of an unknown person. By applying window technique on speech signal, Mel-frequency cepstral coefficients (MFCC) and formants of speech are extracted. With these two kinds of features, we derive a new feature set using cluster based computation. Later a classifier is designed one for each language using the new features vectors and applied on recognition output with a specific apriori knowledge. We use OGI database to perform the experiments and achieved good recognition performance.

Keywords: format frequencies; language identification; Mel cepstral coefficients MFCC; LID; minimum phase group delay; new feature set.

DOI: 10.1504/IJAIP.2025.147911

International Journal of Advanced Intelligence Paradigms, 2025 Vol.30 No.4, pp.273 - 282

Received: 30 Nov 2018
Accepted: 05 Feb 2019
Published online: 08 Aug 2025 *

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