Automatic development of speech-in-noise hearing tests using machine learning
Abstract Understanding speech in noisy environments is a primary challenge for individuals with hearing loss, affecting daily communication and quality of life. Traditional speech-in-noise tests are essential for screening and diagnosing hearing loss but are resource-intensive to develop, making the...
Saved in:
| Main Authors: | Sigrid Polspoel, David R. Moore, De Wet Swanepoel, Sophia E. Kramer, Cas Smits |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-96312-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automatic Speech Recognition Errors Detection And Correction: A Review
by: Rahhal Errattahi, et al.
Published: (2016-05-01) -
Arabic Speech Recognition Based on Encoder-Decoder Architecture of Transformer
by: Mohanad Sameer, et al.
Published: (2023-03-01) -
ECE-TTS: A Zero-Shot Emotion Text-to-Speech Model with Simplified and Precise Control
by: Shixiong Liang, et al.
Published: (2025-05-01) -
Large Language Model-Driven 3D Hyper-Realistic Interactive Intelligent Digital Human System
by: Yanying Song, et al.
Published: (2025-03-01) -
Two-Microphone Dereverberation for Automatic Speech Recognition of Polish
by: Mikolaj KUNDEGORSKI, et al.
Published: (2014-09-01)