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My ICASSP 2019 Schedule

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MLSP-P15: Audio and Speech Applications

Session Type: Poster
Time: Thursday, May 16, 18:00 - 20:00
Location: Poster Area G, East Landing, First Floor
Session Chair: Zhang Tao, Starkey Hearing Technologies
 
  MLSP-P15.1: SPEECH SUPER RESOLUTION GENERATIVE ADVERSARIAL NETWORK
         Sefik Emre Eskimez; University of Rochester
         Kazuhito Koishida; Microsoft Corporation
 
  MLSP-P15.2: NOVEL METRIC LEARNING FOR NON-PARALLEL VOICE CONVERSION
         Nirmesh Shah; DA-IICT, Gandhinagar
         Hemant Patil; DA-IICT, Gandhinagar
 
  MLSP-P15.3: DEEP LEARNING FOR CLASSROOM ACTIVITY DETECTION FROM AUDIO
         Robin Cosbey; Western Washington University
         Allison Wusterbarth; Conversica
         Brian Hutchinson; Western Washington University
 
  MLSP-P15.4: TRANSFERABLE POSITIVE/NEGATIVE SPEECH EMOTION RECOGNITION VIA CLASS-WISE ADVERSARIAL DOMAIN ADAPTATION
         Hao Zhou; The University of Manchester
         Ke Chen; The University of Manchester
 
  MLSP-P15.5: ATTITUDE RECOGNITION USING MULTI-RESOLUTION COCHLEAGRAM FEATURES
         Fasih Haider; The University of Edinburgh
         Saturnino Luz; The University of Edinburgh
 
  MLSP-P15.6: TO REVERSE THE GRADIENT OR NOT: AN EMPIRICAL COMPARISON OF ADVERSARIAL AND MULTI-TASK LEARNING IN SPEECH RECOGNITION
         Yossi Adi; Bar-Ilan University
         Neil Zeghidour; Facebook AI Research and CoML, ENS/INRIA
         Ronan Collobert; Facebook AI Research
         Nicolas Usunier; Facebook AI Research
         Vitaliy Liptchinsky; Facebook AI Research
         Gabriel Synnaeve; Facebook AI Research
 
  MLSP-P15.7: TOWARDS AUTOMATIC METHODS TO DETECT ERRORS IN TRANSCRIPTIONS OF SPEECH RECORDINGS
         Jinyi Yang; Johns Hopkins University
         Lucas Ondel; Brno University of Technology
         Vimal Manohar; Johns Hopkins University
         Hynek Hermansky; Johns Hopkins University
 
  MLSP-P15.8: ONLINE SINGING VOICE SEPARATION USING A RECURRENT ONE-DIMENSIONAL U-NET TRAINED WITH DEEP FEATURE LOSSES
         Clement Doire; Audionamix