REDAT: Accent-Invariant Representation for End-to-End ASR by Domain Adversarial Training with Relabeling

14 December 2020

Papers citing "REDAT: Accent-Invariant Representation for End-to-End ASR by Domain Adversarial Training with Relabeling"

7 / 7 papers shown

Title
Test-Time Training for Speech Sri Harsha Dumpala Chandramouli Shama Sastry Sageev Oore 39 1 0 19 Sep 2023
Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems A case study for Modern Greek Georgios Paraskevopoulos Theodoros Kouzelis Georgios Rouvalis Athanasios Katsamanis V. Katsouros Alexandros Potamianos VLM 25 7 0 31 Dec 2022
Improving generalizability of distilled self-supervised speech processing models under distorted settings Kuan-Po Huang Yu-Kuan Fu Tsung-Yuan Hsu Fabian Ritter Gutierrez Fan Wang Liang-Hsuan Tseng Yu Zhang Hung-yi Lee 32 13 0 14 Oct 2022
Unified Modeling of Multi-Domain Multi-Device ASR Systems Soumyajit Mitra Swayambhu Nath Ray Bharat Padi Arunasish Sen Raghavendra Bilgi Harish Arsikere Shalini Ghosh A. Srinivasamurthy Sri Garimella 37 3 0 13 May 2022
Improving Distortion Robustness of Self-supervised Speech Processing Tasks with Domain Adaptation Kuan Po Huang Yuanbin Fu Yu Zhang Hung-yi Lee 19 28 0 30 Mar 2022
LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects Alexander Johnson Ruchao Fan Robin Morris Abeer Alwan 16 12 0 19 Feb 2022
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding Peter Sullivan Toshiko Shibano Muhammad Abdul-Mageed 38 11 0 10 Feb 2022