Comparing K-means and OPTICS clustering algorithms for identifying vowel categories
نویسندگان
چکیده
The K-means algorithm is the most commonly used clustering method for phonetic vowel description but has some properties that may be sub-optimal representing data. This study compares with an alternative algorithm, OPTICS, in two speech styles (lab vs. conversational) English to test whether OPTICS a viable characterizing spaces. We find noisier data, identifies clusters more accurately represent underlying Our results highlight importance of choosing whose assumptions are line data being considered.
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ژورنال
عنوان ژورنال: Proceedings of the Linguistic Society of America
سال: 2023
ISSN: ['2473-8689']
DOI: https://doi.org/10.3765/plsa.v8i1.5488