Technical Program

AASP-P2: Pitch and Musical Analysis

Session Type: Poster
Time: Monday, March 6, 16:00 - 18:00
Location: Churchill: Poster Area H
Session Chair: Zhiyao Duan,
 
AASP-P2.1: POLYPHONIC PIANO NOTE TRANSCRIPTION WITH NON-NEGATIVE MATRIX FACTORIZATION OF DIFFERENTIAL SPECTROGRAM
         Lufei Gao; The Chinese University of Hong Kong
         Li Su; Academia Sinica
         Yi-Hsuan Yang; Academia Sinica
         Tan Lee; The Chinese University of Hong Kong
 
AASP-P2.2: FUSING TRANSCRIPTION RESULTS FROM POLYPHONIC AND MONOPHONIC AUDIO FOR SINGING MELODY TRANSCRIPTION IN POLYPHONIC MUSIC
         Bilei Zhu; Tencent Youtu AI Lab
         Fuzhang Wu; Tencent Youtu AI Lab
         Ke Li; Tencent Youtu AI Lab
         Yongjian Wu; Tencent Youtu AI Lab
         Feiyue Huang; Tencent Youtu AI Lab
         Yunsheng Wu; Tencent Youtu AI Lab
 
AASP-P2.3: PROBABILISTIC TRANSCRIPTION OF SUNG MELODY USING A PITCH DYNAMIC MODEL
         Luwei Yang; Queen Mary University of London
         Akira Maezawa; Yamaha Corporation
         Jordan B. L. Smith; National Institute of Advanced Industrial Science and Technology
         Elaine Chew; Queen Mary University of London
 
AASP-P2.4: IMPROVED TEMPLATE BASED CHORD RECOGNITION USING THE CRP FEATURE
         Ken O'Hanlon; Queen Mary University of London
         Sebastian Ewert; Queen Mary University of London
         Johan Pauwels; Queen Mary University of London
         Mark B. Sandler; Queen Mary University of London
 
AASP-P2.5: MULTI-PITCH STREAMING OF INTERWOVEN STREAMS
         Chih-Yi Kuan; National Central University
         Li Su; Academia Sinica
         Yu-Hao Chin; National Central University
         Jia-Ching Wang; National Central University
 
AASP-P2.6: AUTOMATIC MUSICAL KEY ESTIMATION WITH ADAPTIVE MODE BIAS
         Gilberto Bernardes; INESC TEC
         Matthew Davies; INESC TEC
         Carlos Guedes; New York University Abu-Dhabi & INESC TEC
 
AASP-P2.7: A REASSIGNED BASED SINGING VOICE PITCH CONTOUR EXTRACTION METHOD
         Georgina Tryfou; Fondazione Bruno Kessler
         Maurizio Omologo; Fondazione Bruno Kessler
 
AASP-P2.8: LYRIC RECOGNITION IN MONOPHONIC SINGING USING PITCH-DEPENDENT DNN
         Dairoku Kawai; Toyohashi University of Technology
         Kazumasa Yamamoto; Toyohashi University of Technology
         Seiichi Nakagawa; Toyohashi University of Technology
 
AASP-P2.9: USING OPTIMAL TRANSPORT FOR ESTIMATING INHARMONIC PITCH SIGNALS
         Filip Elvander; Lund University
         Stefan Ingi Adalbj√∂rnsson; Lund University
         Johan Karlsson; Royal Institute of Technology
         Andreas Jakobsson; Lund University
 
AASP-P2.10: A NOVEL PITCH EXTRACTION BASED ON JOINTLY TRAINED DEEP BLSTM RECURRENT NEURAL NETWORKS WITH BOTTLENECK FEATURES
         Bin Liu; CASIA
         Jianhua Tao; CASIA
         Dawei Zhang; CASIA
         Yibin Zheng; CASIA