most citedASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks

18 citations · 31 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS20203 cited

Single Channel Far Field Feature Enhancement For Speaker Verification In The Wild

Phani Sankar Nidadavolu, Saurabh Kataria, Paola García-Perera +2

We investigated an enhancement and a domain adaptation approach to make speaker verification systems robust to perturbations of far-field speech. In the enhancement approach, using…

eess.AS2020

x-vectors meet emotions: A study on dependencies between emotion and speaker recognition

Raghavendra Pappagari, Tianzi Wang, Jesus Villalba +2

In this work, we explore the dependencies between speaker recognition and emotion recognition. We first show that knowledge learned for speaker recognition can be reused for emotio…

eess.AS20199 cited

Deep neural networks for emotion recognition combining audio and transcripts

Jaejin Cho, Raghavendra Pappagari, Purva Kulkarni +3

In this paper, we propose to improve emotion recognition by combining acoustic information and conversation transcripts. On the one hand, an LSTM network was used to detect emotion…

eess.AS20191 cited

MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation

Suwon Shon, Najim Dehak, Douglas Reynolds +1

The Multi-target Challenge aims to assess how well current speech technology is able to determine whether or not a recorded utterance was spoken by one of a large number of blackli…

cs.CL201918 cited

ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks

Cheng-I Lai, Nanxin Chen, Jesús Villalba +1

We present JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT). Anti-spoofing has gathered more and more at…