31 citations · 66 across the 20 of their papers we have counts for
17 papers · 1 filter
Improving Accented Speech Recognition using Data Augmentation based on Unsupervised Text-to-Speech Synthesis
Cong-Thanh Do, Shuhei Imai, Rama Doddipatla +1
This paper investigates the use of unsupervised text-to-speech synthesis (TTS) as a data augmentation method to improve accented speech recognition. TTS systems are trained with a…
LASER: Learning by Aligning Self-supervised Representations of Speech for Improving Content-related Tasks
Amit Meghanani, Thomas Hain
Self-supervised learning (SSL)-based speech models are extensively used for full-stack speech processing. However, it has been observed that improving SSL-based speech representati…
Automatic Speech Recognition System-Independent Word Error Rate Estimation
Chanho Park, Mingjie Chen, Thomas Hain
Word error rate (WER) is a metric used to evaluate the quality of transcriptions produced by Automatic Speech Recognition (ASR) systems. In many applications, it is of interest to…
Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations
Amit Meghanani, Thomas Hain
Acoustic word embeddings (AWEs) are vector representations of spoken words. An effective method for obtaining AWEs is the Correspondence Auto-Encoder (CAE). In the past, the CAE me…
SCORE: Self-supervised Correspondence Fine-tuning for Improved Content Representations
Amit Meghanani, Thomas Hain
There is a growing interest in cost-effective self-supervised fine-tuning (SSFT) of self-supervised learning (SSL)-based speech models to obtain task-specific representations. Thes…
MUST: A Multilingual Student-Teacher Learning approach for low-resource speech recognition
Muhammad Umar Farooq, Rehan Ahmad, Thomas Hain
Student-teacher learning or knowledge distillation (KD) has been previously used to address data scarcity issue for training of speech recognition (ASR) systems. However, a limitat…