schizophrenia and depression – evidence in speech prosody student: yonatan vaizman advisor: prof....
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Schizophrenia and Depression – Evidence in Speech Prosody
Student: Yonatan VaizmanAdvisor: Prof. Daphna WeinshallJoint work withRoie Kliper and Dr. Shirley Portuguese
Agenda
• Presenting the approach– Speech prosody– Mental states, mental pathologies, Schizophrenia
• Our work– Data– Methods– Results
• Future directions
Information in speech prosody
• Syntactic disambiguation from intonation
• Prosodic content as signal for mental state
Large variabilitywave form spectrogram
Estimating mental states
Previous works
• Voice analysis to detect cancer of the larynx(Murry, T. and E. Doherty 1980)
• Differences in speech between Schizophrenians and normals(e.g. Stassen, H., et al 1995)
Our work - Data
Strict expression Free expression
Reading a list of words
Reading a passage
Free interview
Dr. (M.D.) Shirley Portuguese
Time (sec)Time (sec)
Our work - Methods
• Auditory signal processing• Collecting acoustic features
– Duration features– Variability features– Speech density features
Time (sec)
Acoustic feature extraction
Duration features:
utterance gap
•Mean utterance duration•Mean log utterance duration•Mean gap duration•Mean log gap duration
Acoustic feature extractionVariability features:
Meso scale
Pitch (f0) / period
Variability
Power variability
Shimmer
Jitter
Micro scale
Results – acoustic featuresList of wordsFluent textDuring task
mean jitter score
Results - classification
C vs. SC vs. DS vs. D
List of words0.73810.700.7143
Passage0.80950.690.5200
Interview0.750.87100.7667
ControlSchizophreniaDepression
List of words202220
Passage111015
Interview333129
Sample sizes:
Correct classification rates (LOU):
Linear classification with SVM
Results – classificationseparated by gender
C vs. SC vs. DS vs. D
Both genders0.750.87100.7667
Male only0.68570.73080.4516
Female only0.69230.93330.9231
C vs. SC vs. DS vs. D
Both genders0.73810.700.7143
Male only0.54170.63160.4783
Female only0.88240.75000.6316
List of words:
Interview:
Results – Correlation
Acoustic featureSANS total (cc, p-val)
Utterance duration(-0.5953, 0.0004)
Gap duration(0.4223, 0.0180)
Spoken ratio(-0.5134, 0.0031)
Fragmented speech(-0.4831, 0.0059)
Emphasis(-0.4782, 0.0065)
Inflection(-0.3475, 0.0554)
Acoustic featureHAM-D
Utterance duration(0.4661, 0.0164)
Inflection(-0.5007, 0.0092)
Jitter(-0.4555, 0.0194)
Schizophrenia:
Depression:
Results - summary
• Possible to find signal to mental state in prosodic features
• Local and micro-scale features are discriminative
• Type of speech test influences discrimination• Possibly signal is more prominent in females
Future directions
• Spectral features• Using linguistic elements: phonemes, words• Forced alignment and functional data analysis• Language and speaker identification methods• Personal directions:
– Other signal domains: general sounds, music…
Thank you!