Individual-level patterns in the random forest classification of fricatives in conversational English
Year: 2026
Type: article
Abstract: This study uses a corpus of sociolinguistic interview speech from Western Canadian English to examine individual-level patterns in random forest classification models for fricatives. The models include 23 spectral, durational, and amplitudinal measures commonly used for group-level analyses. Results reveal that measures such as midpoint standard deviation, spectral peak frequency, peak power, and segment duration can capture meaningful distinctions within individual speakers, with some acoustic cues playing a greater role in distinguishing fricatives within speakers than across them. Limiting models to the ten most important predictors slightly increased classification error, suggesting the importance of broader acoustic information.
Source: JASA Express Letters
DOI: 10.1121/10.0042480
Authors: Viktor Kharlamov, Daniel Brenner, Benjamin V. Tucker
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7130412144