With a noise presents in the background and short utterances, MFCC performance could not be reliable without a support feature. To address this, a new feature 'Entrocy' for accurate and robust speaker verification under limited data and noisy environments is proposed and employed to support MFCC coefficients.
Mar 25, 2021
A new feature 'Entrocy' for accurate and robust speaker verification under limited data and noisy environments is proposed and employed to support MFCC ...
The resulting Entrocy features are combined with MFCC functionality to generate a composite feature, which is tested using the Gaussian Mixture Model (GMM) ...
Oct 22, 2024 · With a noise presents in the background and short utterances, MFCC performance could not be reliable without a support feature. To address this, ...
Short utterance and background noise represent great challenging for speaker verification due to the mismatch and limited training and/or retrieve data.
To address this, we propose a new feature 'entrocy' for accurate and robust speaker recognition, which we mainly employ to support MFCC coefficients in noisy ...
Entrocy features are combined with MFCCs to generate a composite feature set which is tested using the gaussian mixture model (GMM) speaker recognition method.
Entrocy features are combined with MFCCs to generate a composite feature set which is tested using the gaussian mixture model (GMM) speaker recognition method.
Missing: Improving short utterance
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Improving short utterance speaker verification by combining MFCC and Entrocy in Noisy conditions. Article 25 March 2021. Robust noise MKMFCC–SVM automatic ...
2021, Improving Short Utterance Speaker Verification By Combining Mfcc And Entrocy In Noisy Conditions, 0.60-0.55 ; 2018, Speaker identification based on ...