Spectral pattern recognition of improved voice quality.
The self-organizing map (a neural network) was applied to the spectral pattern recognition of voice quality in 34 subjects: 15 patients operated on because of insufficient glottal closure and 19 subjects not treated for voice disorders. The voice samples, segments of sustained /a/, were perceptually rated by six experts. A self-organized acoustic feature map was first computed from tokens of /a/ and then used for the analysis of the samples. The locations of the samples on the map were determined and the distances from a normal reference were compared with the perceptual ratings. The map locations corresponded to the degree of audible disorder: the samples judged as normal were overlapping or close to the normal reference, whereas the samples judged as dysphonic were located further away from it. The comparison of pre- and postoperative samples of the patients showed that the perceived improvement of voice quality was also detected by the map.
Rihkanen
H
H
Department of Otorhinolaryngology, Helsinki University Central Hospital, Finland.
Leinonen
L
L
Hiltunen
T
T
Kangas
J
J
D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010700:Phonetics; D013018:Sound Spectrography; D013061:Speech Acoustics; D014832:Voice Disorders / Q000628:therapy*; D014833:Voice Quality; D014834:Voice Training