Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition

21 October 2021

Papers citing "Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition"

5 / 5 papers shown

Title
Denoising LM: Pushing the Limits of Error Correction Models for Speech Recognition Zijin Gu Tatiana Likhomanenko Richard He Bai Erik McDermott R. Collobert Navdeep Jaitly AuLLM 43 2 0 24 May 2024
Text-only domain adaptation for end-to-end ASR using integrated text-to-mel-spectrogram generator Vladimir Bataev Roman Korostik Evgeny Shabalin Vitaly Lavrukhin Boris Ginsburg VLM 10 14 0 27 Feb 2023
The NPU-ASLP System for The ISCSLP 2022 Magichub Code-Swiching ASR Challenge Yuhao Liang Pei-Ning Chen F. Yu Xinfa Zhu Tianyi Xu Linfu Xie 13 0 0 26 Oct 2022
Style Equalization: Unsupervised Learning of Controllable Generative Sequence Models Jen-Hao Rick Chang A. Shrivastava H. Koppula Xiaoshuai Zhang Oncel Tuzel DiffM 38 15 0 06 Oct 2021
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis Ye Jia Yu Zhang Ron J. Weiss Quan Wang Jonathan Shen ... Z. Chen Patrick Nguyen Ruoming Pang Ignacio López Moreno Yonghui Wu 196 817 0 12 Jun 2018