4 papers
CHiME-9 ECHI: A Machine Learning Challenge for Enhancing Conversations to Address Hearing Impairment
Robert Sutherland, Thomas Kuebert, Marko Lugger +6
This work presents the task and results of the CHiME-9 challenge for Enhancing Conversations to address Hearing Impairment. The challenge considers the scenario of four-party conve…
Challenges of Multi-Speaker Extraction for Real Conversational Speech Enhancement
Robert Sutherland, Stefan Goetze, Jon Barker
Target-speaker and multi-speaker extraction are techniques for extracting speech from a desired speaker or desired speakers in the presence of other speakers and/or noise. Neural n…
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…
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…