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Speech based emotional and depressive mental state prediction using Gaussian Process state-space models

Research Project

Project/Area Number 15K00243
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Perceptual information processing
Research InstitutionThe University of Aizu

Principal Investigator

Markov Konstantin  会津大学, コンピュータ理工学部, 上級准教授 (80394998)

Co-Investigator(Kenkyū-buntansha) 松井 知子  統計数理研究所, モデリング研究系, 教授 (10370090)
Project Period (FY) 2015-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
KeywordsSpeech emotion / Neural Networks / Gaussian Process / Personality Recogniition / Music emotion / Personality Recognition / Speech Emotion / State-Space Model / Particle filter
Outline of Final Research Achievements

Estimating the emotional state of a person is an important task with applications in medicine, social interaction as well as in services industry. On the other hand, recognition of the person personality is even more challenging task which includes emotion estimation as one of its components. In this research, we used latest developments and technologies in signal processing and machine learning fields to build several systems for emotion recognition from speech and music as well as text based personality recognition system. The used methods and technologies include Gaussian Processes, non-linear state-space models and deep neural networks.
During the last year of this research, we focused on personality recognition task and built a system based on deep neural networks capable of recognizing the five personality traits with high accuracy. Our findings are published in the IEEE Access journal and several international conferences.

Report

(4 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Research-status Report
  • 2015 Research-status Report
  • Research Products

    (5 results)

All 2017 2016 2015

All Presentation (4 results) (of which Int'l Joint Research: 3 results) Book (1 results)

  • [Presentation] Deep learning based personality recognition from Facebook status updates2017

    • Author(s)
      J.Yu, K.Markov
    • Organizer
      IEEE 8th Int. Conf. on Awareness Science and Technology
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Articulatory and Spectrum Features Integration using Generalized Distillation Framework2016

    • Author(s)
      J.Yu, K.Markov, T.Matsui
    • Organizer
      IEEE Int. Workshop on Machine Learning for Signal Processing
    • Place of Presentation
      Salerno, Italy
    • Year and Date
      2016-09-13
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] Robust Speech Recognition using Generalized Distillation Framework2016

    • Author(s)
      K.Markov, T.Matsui
    • Organizer
      Interspeech
    • Place of Presentation
      San Francisco, USA
    • Year and Date
      2016-09-08
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] Dynamic Speech Emotion Recognition with State-Space Models2015

    • Author(s)
      Konstantin Markov, Tomoko Matsui
    • Organizer
      European Signal Processing Conference
    • Place of Presentation
      Nice, France
    • Year and Date
      2015-08-31
    • Related Report
      2015 Research-status Report
  • [Book] Modern Methodology and Applications in Spatial-Temporal Modeling, Chapter 32015

    • Author(s)
      Konstantin Markov, Tomoko Matsui
    • Total Pages
      109
    • Publisher
      Springer
    • Related Report
      2015 Research-status Report

URL: 

Published: 2015-04-16   Modified: 2019-03-29  

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