A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection
Vyom Verma,
Anish Benjwal,
Amit Chhabra
et al.
Abstract:Voice is an essential component of human communication, serving as a fundamental medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory patterns can lead to voice disorders, which can have a profound impact on interpersonal interactions. Early detection of voice disorders is crucial for improving voice health and quality of life. This research proposes a novel methodology called VDDMFS [voice disorder detection using MFCC (Mel-frequency cepstral coefficients), fundamental freq… Show more
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