IEEE ICASSP 2022

2022 IEEE International Conference on Acoustics, Speech and Signal Processing

7-13 May 2022
  • Virtual (all paper presentations)
22-27 May 2022
  • Main Venue: Marina Bay Sands Expo & Convention Center, Singapore
27-28 October 2022
  • Satellite Venue: Crowne Plaza Shenzhen Longgang City Centre, Shenzhen, China

ICASSP 2022
SPE-86.4

CUSTOMER SATISFACTION ESTIMATION USING UNSUPERVISED REPRESENTATION LEARNING WITH MULTI-FORMAT PREDICTION LOSS

Atsushi Ando, Yumiko Murata, Ryo Masumura, Satoshi Suzuki, Naoki Makishima, Takafumi Moriya, Takanori Ashihara, Hiroshi Sato, NTT Corporation, Japan

Session:
Speech Paralinguistics: Representation Learning

Track:
Speech and Language Processing

Location:
Gather Area B

Presentation Time:
Fri, 13 May, 22:00 - 22:45 China Time (UTC +8)
Fri, 13 May, 14:00 - 14:45 UTC

Session Co-Chairs:
Mathew Magimai Doss, Idiap Research Institute and Jibin Wu, National University of Singapore
Presentation
Discussion
Resources
Session SPE-86
SPE-86.1: MODELING OF PRE-TRAINED NEURAL NETWORK EMBEDDINGS LEARNED FROM RAW WAVEFORM FOR COVID-19 INFECTION DETECTION
Zohreh Mostaani, RaviShankar Prasad, Bogdan Vlasenko, Mathew Magimai Doss, Idiap Research Institute, Switzerland
SPE-86.2: DUAL ATTENTION POOLING NETWORK FOR RECORDING DEVICE CLASSIFICATION USING NEUTRAL AND WHISPERED SPEECH
Abinay Reddy Naini, Prasanta Kumar Ghosh, Indian Institute of Science, Bangalore, India; Bhavuk Singhal, Information Technology, Bundelkhand Institute of Engineering and Technology, Jhansi, India, India
SPE-86.3: ENTRAINMENT ANALYSIS FOR ASSESSMENT OF AUTISTIC SPEECH PROSODY USING BOTTLENECK FEATURES OF DEEP NEURAL NETWORK
Keiko Ochi, Kyoto University, Japan; Nobutaka Ono, Tokyo Metropolitan University, Japan; Keiho Owada, Miho Kuroda, Shigeki Sagayama, University of Tokyo, Japan; Hidenori Yamasue, Hamamatsu University School of Medicine, Japan
SPE-86.4: CUSTOMER SATISFACTION ESTIMATION USING UNSUPERVISED REPRESENTATION LEARNING WITH MULTI-FORMAT PREDICTION LOSS
Atsushi Ando, Yumiko Murata, Ryo Masumura, Satoshi Suzuki, Naoki Makishima, Takafumi Moriya, Takanori Ashihara, Hiroshi Sato, NTT Corporation, Japan
SPE-86.5: Automatic Assessment of the Degree of Clinical Depression from Speech Using X-Vectors
José Vicente Egas-López, University of Szeged, Hungary; Gábor Kiss, Sztahó David, Budapest University of Technology and Economics, Hungary; Gábor Gosztolya, MTA-SZTE Research Group on Artificial Intelligence, Hungary
SPE-86.6: AUTOMATIC DEPRESSION LEVEL ASSESSMENT FROM SPEECH BY LONG-TERM GLOBAL INFORMATION EMBEDDING
Ya Li, Beijing University of Posts and Telecommunications, China; Mingyue Niu, Ziping Zhao, Tianjin Normal University, China; Jianhua Tao, Institute of Automation, Chinese Academy of Sciences, China