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20152026
most citedASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks

18 citations · 56 across the 44 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

eess.AS2019

Speaker detection in the wild: Lessons learned from JSALT 2019

Paola Garcia, Jesus Villalba, Herve Bredin +21

This paper presents the problems and solutions addressed at the JSALT workshop when using a single microphone for speaker detection in adverse scenarios. The main focus was to tack…

eess.AS2019

Listen and Fill in the Missing Letters: Non-Autoregressive Transformer for Speech Recognition

Nanxin Chen, Shinji Watanabe, Jesús Villalba +1

Recently very deep transformers have outperformed conventional bi-directional long short-term memory networks by a large margin in speech recognition. However, to put it into produ…

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.AS2019

Low-Resource Domain Adaptation for Speaker Recognition Using Cycle-GANs

Phani Sankar Nidadavolu, Saurabh Kataria, Jesús Villalba +1

Current speaker recognition technology provides great performance with the x-vector approach. However, performance decreases when the evaluation domain is different from the traini…

cs.CL2019

Hierarchical Transformers for Long Document Classification

Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2

BERT, which stands for Bidirectional Encoder Representations from Transformers, is a recently introduced language representation model based upon the transfer learning paradigm. We…

eess.AS2019

Unsupervised Feature Enhancement for speaker verification

Phani Sankar Nidadavolu, Saurabh Kataria, Jesús Villalba +2

The task of making speaker verification systems robust to adverse scenarios remain a challenging and an active area of research. We developed an unsupervised feature enhancement ap…