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My ICASSP 2017 Schedule

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SP-P2: Emotion Recognition II

Session Type: Poster
Time: Monday, March 6, 13:30 - 15:30
Location: Churchill: Poster Area B
Session Chair: Julia Hirschberg, Columbia Uniiversity
 
  SP-P2.1: A FIRST LOOK INTO A CONVOLUTIONAL NEURAL NETWORK FOR SPEECH EMOTION DETECTION
         Dario Bertero; The Hong Kong University of Science and Technology
         Pascale Fung; The Hong Kong University of Science and Technology
 
  SP-P2.2: EFFECTIVE EMOTION RECOGNITION IN MOVIE AUDIO TRACKS
         Margarita Kotti; Toshiba Research Europe Ltd.
         Yannis Stylianou; Toshiba Research Europe Ltd.
 
  SP-P2.3: MOOD DETECTION FROM DAILY CONVERSATIONAL SPEECH USING DENOISING AUTOENCODER AND LSTM
         Kun-Yi Huang; National Cheng Kung University
         Chung-Hsien Wu; National Cheng Kung University
         Ming-Hsiang Su; National Cheng Kung University
         Hsiang-Chi Fu; National Cheng Kung University
 
  SP-P2.4: AUTOMATIC DYNAMIC TEMPLATE TRACKING OF INNER LIPS BASED ON CLNF
         Li Liu; Gipsa-lab, France
         Gang Feng; Gipsa-lab, France
         Denis Beautemps; Gipsa-lab, France
 
  SP-P2.5: BIOLOGICALLY INSPIRED SPEECH EMOTION RECOGNITION
         Reza Lotfidereshgi; Université de Sherbrooke
         Philippe Gournay; Université de Sherbrooke
 
  SP-P2.6: DETECTING STRESS AND DEPRESSION IN ADULTS WITH APHASIA THROUGH SPEECH ANALYSIS
         Stephanie Gillespie; Georgia Institute of Technology
         Elliot Moore II; Georgia Institute of Technology
         Jacqueline Laures-Gore; Georgia State University
         Matthew Farina; Georgia State University
         Scott Russell; Grady Memorial Hospital
         Yash-Yee Logan; Georgia Institute of Technology
 
  SP-P2.7: A PLLR AND MULTI-STAGE STAIRCASE REGRESSION FRAMEWORK FOR SPEECH-BASED EMOTION PREDICTION
         Zhaocheng Huang; The University of New South Wales
         Julien Epps; The University of New South Wales
 
  SP-P2.8: LEARNING UTTERANCE-LEVEL REPRESENTATIONS FOR SPEECH EMOTION AND AGE/GENDER RECOGNITION USING DEEP NEURAL NETWORKS
         Zhong-Qiu Wang; The Ohio State University
         Ivan J. Tashev; Microsoft Research
 
  SP-P2.9: AUTOMATIC MULTI-LINGUAL AROUSAL DETECTION FROM VOICE APPLIED TO REAL PRODUCT TESTING APPLICATIONS
         Florian Eyben; audEERING GmbH
         Matthias Unfried; GfK-Nuernberg e.V.
         Gerhard Hagerer; University of Passau
         Björn Schuller; Imperial College London
 
  SP-P2.10: INCREMENTAL ADAPTATION USING ACTIVE LEARNING FOR ACOUSTIC EMOTION RECOGNITION
         Mohammed Abdelwahab; The University of Texas at Dallas
         Carlos Busso; The University of Texas at Dallas