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Showing papers by "Goutam Saha published in 2018"


Journal ArticleDOI
TL;DR: The authors present an extensive survey of SV with short utterances considering the studies from recent past and include latest research offering various solutions and analyses to address the limited data issue within the scope of SV.
Abstract: Automatic speaker verification (ASV) technology now reports a reasonable level of accuracy in its applications in voice-based biometric systems. However, it requires adequate amount of speech data for enrolment and verification; otherwise, the performance becomes considerably degraded. For this reason, the trade-off between the convenience and security is difficult to maintain in practical scenarios. The utterance duration remains a critical issue while deploying a voice biometric system in real-world applications. A large amount of research work has been carried out to address the limited data issue within the scope of SV. The advancements and research activities in mitigating the challenges due to short utterance have seen a significant rise in recent times. In this study, the authors present an extensive survey of SV with short utterances considering the studies from recent past and include latest research offering various solutions and analyses. The review also summarises the major findings of the studies of duration variability problem in ASV systems. Finally, they discuss a number of possible future directions promoting further research in this field.

93 citations


Journal ArticleDOI
TL;DR: This paper proposed a new approach to detect synthetic speech using score-level fusion of front-end features namely, constant Q cepstral coefficients (CQCCs), all-pole group delay function (APGDF) and fundamental frequency variation (FFV), which outperforms all existing baseline features for both known and unknown attacks.

47 citations


Journal ArticleDOI
TL;DR: A novel method of detection of artifact in heart sound is presented which uses a fusion of tunable Q-wavelet transform and signal second difference with median filter to detect the artifact-infected sub-sequences.

11 citations