40 citations · 71 across the 9 of their papers we have counts for
9 papers
Decoding Imagined Speech using Wavelet Features and Deep Neural Networks
Jerrin Thomas Panachakel, A. G. Ramakrishnan
This paper proposes a novel approach that uses deep neural networks for classifying imagined speech, significantly increasing the classification accuracy. The proposed approach emp…
A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG
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 t…
Subjective and objective experiments on the influence of speaker's gender on the unvoiced segments
A Madhavaraj, T V Ananthapadmanabha, A G Ramakrishnan
Subjective and objective experiments are conducted to understand the extent to which a speaker's gender influences the acoustics of unvoiced (U) sounds. U segments of utterances ar…
Adaptive dictionary based approach for background noise and speaker classification and subsequent source separation
K V Vijay Girish, A G Ramakrishnan, T V Ananthapadmanabha
A judicious combination of dictionary learning methods, block sparsity and source recovery algorithm are used in a hierarchical manner to identify the noises and the speakers from…
Intrinsic normalization and extrinsic denormalization of formant data of vowels
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. This reduces the in…
A dictionary learning and source recovery based approach to classify diverse audio sources
K V Vijay Girish, T V Ananthapadmanabha, A G Ramakrishnan
A dictionary learning based audio source classification algorithm is proposed to classify a sample audio signal as one amongst a finite set of different audio sources. Cosine simil…
Significance of the levels of spectral valleys with application to front/back distinction of vowel sounds
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. The meas…
An Interesting Property of LPCs for Sonorant Vs Fricative Discrimination
T. V. Ananthapadmanabha, A. G. Ramakrishnan, Pradeep Balachandran
Linear prediction (LP) technique estimates an optimum all-pole filter of a given order for a frame of speech signal. The coefficients of the all-pole filter, 1/A(z) are referred to…
Detection of transitions between broad phonetic classes in a speech signal
T V Ananthapadmanabha, K V Vijay Girish, A G Ramakrishnan
Detection of transitions between broad phonetic classes in a speech signal is an important problem which has applications such as landmark detection and segmentation. The proposed…