The Role of Rhythm and Vowel Space in Speech Recognition

This paper explores the role of rhythm and vowel space in automatic speech recognition (ASR), with a particular focus on Midland and Southern American English in the Appalachian region. Three sets of analysis were conducted. First, we computed the word error rates between the ground truth and the transcripts generated by DARLA. Consistent with previous studies, the results show higher error rates for Southern English (59.5%) than for Midland English (47.2%), suggesting a dialect gap in speech recognition. Next, we examined whether the error rates are influenced by rhythm. The results show that neither %V nor ΔV reliably predicted ASR performance. We also sought to draw a link between vowel space, speech intelligibility, and ASR performance. Three vowel space metrics were considered: convex hull, formant dispersion, and the polygon area. We noticed that as convex hull and formant dispersion increase, the error rates decrease, particularly for Midland speakers. This aligns with our hypothesis that more expanded vowel space enhances speech intelligibility, thus reducing the error rate for the Midland cohort. No clear connection between the polygon area, speech intelligibility, and error rates was found. These results, albeit suggestive, point out some promising directions for improving acoustic modeling in speech recognition.