Which Utterance Types Are Most Suitable to Detect Hypernasality Automatically?
نویسندگان
چکیده
Automatic tools to detect hypernasality have been traditionally designed analyze sustained vowels exclusively. This is in sharp contrast with clinical recommendations, which consider it necessary use a variety of utterance types (e.g., repeated syllables, sounds, sentences, etc.) study explores the feasibility detecting automatically based on speech samples other than vowels. The participants were 39 patients and healthy controls. Six utterances used: counting 1-to-10 repetition syllable sequences, consonants, vowel, words sentences. recordings obtained, help mobile app, from Spain, Chile Ecuador. Multiple acoustic features computed each MFCC, formant frequency) After selection process, best 20 served train different classification algorithms. Accuracy was highest sequences also some increased slightly by training classifiers between two three utterances. However, results obtained combining multiple classifiers. We conclude that protocols for automatic evaluation should include types. It seems feasible devices.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11198809