most citedOptimal Gaussian Filter for Effective Noise Filtering

3 citations · 13 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2015

Online Handwritten Devanagari Stroke Recognition Using Extended Directional Features

Lajish VL, Sunil Kumar Kopparapu

This paper describes a new feature set, called the extended directional features (EDF) for use in the recognition of online handwritten strokes. We use EDF specifically to recogniz…

cs.CL20143 cited

Modified Mel Filter Bank to Compute MFCC of Subsampled Speech

Kiran Kumar Bhuvanagiri, Sunil Kumar Kopparapu

Mel Frequency Cepstral Coefficients (MFCCs) are the most popularly used speech features in most speech and speaker recognition applications. In this work, we propose a modified Mel…

cs.CV20141 cited

A Framework for On-Line Devanagari Handwritten Character Recognition

Sunil Kumar Kopparapu, Lajish V. L

The main challenge in on-line handwritten character recognition in Indian lan- guage is the large size of the character set, larger similarity between different characters in the s…

cs.SD20143 cited

On the use of Stress information in Speech for Speaker Recognition

Laxmi Narayana M., Sunil Kumar Kopparapu

The performance of a speaker recognition system decreases when the speaker is under stress or emotion. In this paper we explore and identify a mechanism that enables use of inheren…

cs.SD20143 cited

Choice of Mel Filter Bank in Computing MFCC of a Resampled Speech

Laxmi Narayana M., Sunil Kumar Kopparapu

Mel Frequency Cepstral Coefficients (MFCCs) are the most popularly used speech features in most speech and speaker recognition applications. In this paper, we study the effect of r…

cs.OH20143 cited

Optimal Gaussian Filter for Effective Noise Filtering

Sunil Kopparapu, M Satish

In this paper we show that the knowledge of noise statistics contaminating a signal can be effectively used to choose an optimal Gaussian filter to eliminate noise. Very specifical…