On the Relationship between Accent Strength and Articulatory Features
This work contributes to automated accent analysis and articulatory modeling for speech processing applications, but it is incremental as it applies existing methods to new data.
The paper tackled the problem of quantifying accent strength by correlating it with articulatory features inferred from acoustic speech, finding that tongue positioning patterns distinguish American and British English dialects, with notable differences in rhotic and low back vowels.
This paper explores the relationship between accent strength and articulatory features inferred from acoustic speech. To quantify accent strength, we compare phonetic transcriptions with transcriptions based on dictionary-based references, computing phoneme-level difference as a measure of accent strength. The proposed framework leverages recent self-supervised learning articulatory inversion techniques to estimate articulatory features. Analyzing a corpus of read speech from American and British English speakers, this study examines correlations between derived articulatory parameters and accent strength proxies, associating systematic articulatory differences with indexed accent strength. Results indicate that tongue positioning patterns distinguish the two dialects, with notable differences inter-dialects in rhotic and low back vowels. These findings contribute to automated accent analysis and articulatory modeling for speech processing applications.