We explore the impact of speech- and speaker-specific modeling onto the Modulation Spectrum Analysis – Kolmogorov- Smirnov feature Testing (MSA-KST) characterization method in the task of automated prediction of the cognitive impairment diagnosis, namely dysphasia and pervasive development disorder. Phoneme-synchronous capturing of speech dynamics is a reasonable choice for a segmental speech characterization system as it allows comparing speech dynamics in the similar phonetic contexts. Speaker-specific modeling aims at reducing the “within-the-class” variability of the characterized speech or speaker population by removing the effect of speaker properties that should have no relation to the characterization. Specifically the vocal tract length of a speaker has nothing to do with the diagnosis attribution and, thus, the feature set shall be normalized accordingly. The resulting system compares favorably to the baseline system of the Interspeech’2013 Computational Paralinguistics Challenge.

PHONETIC AND ANTHROPOMETRIC CONDITIONING OF MSA-KST COGNITIVE IMPAIRMENT CHARACTERIZATION SYSTEM

Jalalvand, Shahab;Gretter, Roberto;Falavigna, Giuseppe Daniele
2013-01-01

Abstract

We explore the impact of speech- and speaker-specific modeling onto the Modulation Spectrum Analysis – Kolmogorov- Smirnov feature Testing (MSA-KST) characterization method in the task of automated prediction of the cognitive impairment diagnosis, namely dysphasia and pervasive development disorder. Phoneme-synchronous capturing of speech dynamics is a reasonable choice for a segmental speech characterization system as it allows comparing speech dynamics in the similar phonetic contexts. Speaker-specific modeling aims at reducing the “within-the-class” variability of the characterized speech or speaker population by removing the effect of speaker properties that should have no relation to the characterization. Specifically the vocal tract length of a speaker has nothing to do with the diagnosis attribution and, thus, the feature set shall be normalized accordingly. The resulting system compares favorably to the baseline system of the Interspeech’2013 Computational Paralinguistics Challenge.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/206018
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact