A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG

no code implementations • 19 Mar 2020 • Jerrin Thomas Panachakel, A. G. Ramakrishnan, T. V. Ananthapadmanabha

The recent advances in the field of deep learning have not been fully utilised for decoding imagined speech primarily because of the unavailability of sufficient training samples to train a deep network.

EEG

Intrinsic normalization and extrinsic denormalization of formant data of vowels

no code implementations • 16 Sep 2016 • T. V. Ananthapadmanabha, A. G. Ramakrishnan

Using a known speaker-intrinsic normalization procedure, formant data are scaled by the reciprocal of the geometric mean of the first three formant frequencies.

General Classification Vowel Classification

Significance of the levels of spectral valleys with application to front/back distinction of vowel sounds

no code implementations • 16 Jun 2015 • T. V. Ananthapadmanabha, A. G. Ramakrishnan, Shubham Sharma

An objective critical distance (OCD) has been defined as that spacing between adjacent formants, when the level of the valley between them reaches the mean spectral level.