Discrimination between patients with CVDs and healthy people by voiceprint using the MFCC and Pitch
Diagnostyka, 2021 Heart diseases cause many deaths around the world every year, and his death rate makes him the leader of the killer diseases. But early diagnosis can be helpful to decrease those several deaths and save lives.
Abdelhamid Bourouhou +3 more
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Statistically Significant Duration-Independent-based Noise-Robust Speaker Verification [PDF]
International Journal of Mathematical, Engineering and Management SciencesA speaker verification system models individual speakers using different speech features to improve their robustness. However, redundant features degrade the system's performance.
Asmita Nirmal +2 more
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Speech depression recognition based on attentional residual network
Frontiers in Bioscience-Landmark, 2021 Background: Depressive disorder is a common affective disorder, also known as depression, which is characterized by sadness, loss of interest, feelings of guilt or low self-worth and poor concentration.
Xiaoyong Lu +3 more
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Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling. [PDF]
Dev SciABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Famularo RL +3 more
europepmc +2 more sources
Speaker Recognition Systems in the Last Decade – A Survey [PDF]
Engineering and Technology Journal, 2021 Speaker Recognition Defined by the process of recognizing a person by his\her voice through specific features that extract from his\her voice signal. An Automatic Speaker recognition (ASP) is a biometric authentication system.
Ahmed M. Ahmed, Aliaa K. Hassan
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Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC
International Journal of Computer Applications, 2011 Front-end or feature extractor is the first component in an automatic speaker recognition system. Feature extraction transforms the raw speech signal into a compact but effective representation that is more stable and discriminative than the original signal.
E.G. Rajan, Satyanand Singh
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Доклады Белорусского государственного университета информатики и радиоэлектроники, 2022 The paper describes an approach to design a system for analyzing and classification of a voice signal based on perturbation parameters and cepstral representation.
M. I. Vashkevich +2 more
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Evaluation Of Mfcc Estimation Techniques For Music Similarity [PDF]
, 2006 Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Jensen, Jesper Højvang +3 more
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Whispered Speech Conversion Based on the Inversion of Mel Frequency Cepstral Coefficient Features
Algorithms, 2022 A conversion method based on the inversion of Mel frequency cepstral coefficient (MFCC) features was proposed to convert whispered speech into normal speech.
Qiang Zhu +3 more
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SPEAKER IDENTIFICATION FOR ISOLATED GUJARATI DIGITS USING MFCC AND VQ [PDF]
ICTACT Journal on Soft Computing, 2019 The research presented in this paper is part of an ongoing investigation of speaker identification for Gujarati isolated digit. In our previous work, we evaluated feature extraction method of Gujarati isolated digit for speaker identification using Mel ...
Pooja Prajapati, Miral Patel
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