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Acoustic analysis of voice has the potential to expedite detection and diagnosis of voice disorders. Applying an image‐based, neural‐network approach to analyzing the acoustic signal may be an effective means… Click to show full abstract
Acoustic analysis of voice has the potential to expedite detection and diagnosis of voice disorders. Applying an image‐based, neural‐network approach to analyzing the acoustic signal may be an effective means for detecting and differentially diagnosing voice disorders. The purpose of this study is to provide a proof‐of‐concept that embedded data within human phonation can be accurately and efficiently decoded with deep learning neural network analysis to differentiate between normal and disordered voices.
Keywords:
decoding phonation;
proof concept;
proof;
phonation artificial
Journal Title: Laryngoscope Investigative Otolaryngology
Year Published: 2019
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Journal Title: Laryngoscope Investigative Otolaryngology
Year Published: 2019
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!