1 citations · 1 across the 3 of their papers we have counts for
3 papers
Using Speech Foundational Models in Loss Functions for Hearing Aid Speech Enhancement
Robert Sutherland, George Close, Thomas Hain +2
Machine learning techniques are an active area of research for speech enhancement for hearing aids, with one particular focus on improving the intelligibility of a noisy speech sig…
Transcription-Free Fine-Tuning of Speech Separation Models for Noisy and Reverberant Multi-Speaker Automatic Speech Recognition
William Ravenscroft, George Close, Stefan Goetze +4
One solution to automatic speech recognition (ASR) of overlapping speakers is to separate speech and then perform ASR on the separated signals. Commonly, the separator produces art…
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…