Although humans excel at speech recognition, recognition accuracy can vary widely due to differences in background environments as well as the speaker's voice quality, intonation, and pitch. Predicting when speech recognition will succeed or fail, however, remains an ongoing challenge in hearing research....
✦ Clinical Takeaway ✦
This preprint offers a potentially valuable acoustic framework for predicting speech-in-noise performance, but findings require peer review and clinical validation before influencing hearing aid fitting or speech-in-noise test selection.
✦ Why It Matters ✦
A robust acoustic predictor of speech recognition in noise could transform how clinicians and engineers evaluate and design hearing devices and diagnostic speech tests.
✦ Key Points ✦
- 01Modulation statistics (patterns of how sound fluctuates over time) predict speech recognition accuracy.
- 02