SOURCE-LINKED INTELLIGENCE
Quantifying Consonant Contributions to Word Intelligibility via Acoustic Masking
Consonants contribute unequally to whether a word is understood. Given the limited time available for therapy, ranking consonants by contribution to intelligibility helps prioritize intervention targets in motor speech disorders. However, measuring this contribution relies on perceptual studies that are difficult to scale. This paper presents a scalable method that measures consonant contribution using acoustic masking. We silence one consonant at a time in an isolated word and test whether an automatic speech recognition (ASR) model still recognizes the word. We define a consonant's contribut
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T18:49:21.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.