TitaNet: Neural Model for Speaker Representation with 1D Depth-Wise Separable Convolutions and Global Context-Reference-Cited by-同舟云学术

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TitaNet: Neural Model for Speaker Representation with 1D Depth-Wise Separable Convolutions and Global Context

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Koluguri Nithin Rao¹,Park Taejin¹,Ginsburg Boris¹

Affiliation:

1. NVIDIA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746806.pdf?arnumber=9746806

Reference31 articles.

1. Nemo: a toolkit for building ai applications using neural modules;kuchaiev,2019

2. BUT system description to voxceleb speaker recognition challenge 2019;zeinali,2019

3. ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context

4. ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification

5. Bayesian speaker verification with heavy-tailed priors;kenny;Odyssey,2010

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