most citedSingle Channel Far Field Feature Enhancement For Speaker Verification In The Wild

3 citations · 3 across the 1 of their papers we have counts for

collaborators

6 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

Analysis of Deep Feature Loss based Enhancement for Speaker Verification

Saurabh Kataria, Phani Sankar Nidadavolu, Jesús Villalba +1

Data augmentation is conventionally used to inject robustness in Speaker Verification systems. Several recently organized challenges focus on handling novel acoustic environments.…

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

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…

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…

eess.AS2019

Feature Enhancement with Deep Feature Losses for Speaker Verification

Saurabh Kataria, Phani Sankar Nidadavolu, Jesús Villalba +3

Speaker Verification still suffers from the challenge of generalization to novel adverse environments. We leverage on the recent advancements made by deep learning based speech enh…