2 citations · 2 across the 4 of their papers we have counts for
4 papers
Self-Train Before You Transcribe
Robert Flynn, Anton Ragni
When there is a mismatch between the training and test domains, current speech recognition systems show significant performance degradation. Self-training methods, such as noisy st…
Training Data Augmentation for Dysarthric Automatic Speech Recognition by Text-to-Dysarthric-Speech Synthesis
Wing-Zin Leung, Mattias Cross, Anton Ragni +1
Automatic speech recognition (ASR) research has achieved impressive performance in recent years and has significant potential for enabling access for people with dysarthria (PwD) i…
Non-Intrusive Speech Intelligibility Prediction for Hearing-Impaired Users using Intermediate ASR Features and Human Memory Models
Rhiannon Mogridge, George Close, Robert Sutherland +4
Neural networks have been successfully used for non-intrusive speech intelligibility prediction. Recently, the use of feature representations sourced from intermediate layers of pr…
Energy-Based Models For Speech Synthesis
Wanli Sun, Zehai Tu, Anton Ragni
Recently there has been a lot of interest in non-autoregressive (non-AR) models for speech synthesis, such as FastSpeech 2 and diffusion models. Unlike AR models, these models do n…