AASP-P6: Audio and speech quality and intelligibility measures; Music analysis 1
Wed, 17 Apr, 08:20 - 10:20 (UTC +9)
Location: Poster Zone 6A
Session Type: Poster
Session Co-Chairs: Michael Mandel, The Graduate School and University Center of The City University of New York and Juhan Nam, Korea Advanced Institute of Science and Technology
Track: Audio and Acoustic Signal Processing
Click the to view the manuscript on IEEE Xplore Open Preview
 

AASP-P6.1: NON-INTRUSIVE SPEECH INTELLIGIBILITY PREDICTION FOR HEARING-IMPAIRED USERS USING INTERMEDIATE ASR FEATURES AND HUMAN MEMORY MODELS
Rhiannon Mogridge, George Close, Robert Sutherland, Thomas Hain, Jon Barker, Stefan Goetze, Anton Ragni, University of Sheffield, United Kingdom of Great Britain and Northern Ireland
 

AASP-P6.2: CORN: CO-TRAINED FULL- AND NO-REFERENCE SPEECH QUALITY ASSESSMENT
Pranay Manocha, Princeton University, United States of America; Donald Williamson, The Ohio State University, United States of America; Adam Finkelstein, Princeton University, United States of America
 

AASP-P6.3: MULTI-TASK PSEUDO-LABEL LEARNING FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT MODEL
Ryandhimas Zezario, Academia Sinica, Taiwan; Bo-Ren Brian Bai, Fortemedia, Taiwan, Taiwan; Chiou-Shann Fuh, National Taiwan University, Taiwan; Hsin-Min Wang, Yu Tsao, Academia Sinica, Taiwan
 

AASP-P6.4: NON-INTRUSIVE SPEECH QUALITY ASSESSMENT WITH MULTI-TASK LEARNING BASED ON TENSOR NETWORK
Hanyue Liu, Miao Liu, Jing Wang, Xiang Xie, Beijing Institute of Technology, China; Lidong Yang, Inner Mongolia University of Science and Technology, China
 

AASP-P6.5: NOMAD: UNSUPERVISED LEARNING OF PERCEPTUAL EMBEDDINGS FOR SPEECH ENHANCEMENT AND NON-MATCHING REFERENCE AUDIO QUALITY ASSESSMENT
Alessandro Ragano, University College Dublin, Ireland; Jan Skoglund, Google LLC, United States of America; Andrew Hines, University College Dublin, Ireland
 

AASP-P6.6: SPEECH FOUNDATION MODELS ON INTELLIGIBILITY PREDICTION FOR HEARING-IMPAIRED LISTENERS
Santiago Cuervo, Ricard Marxer, Université de Toulon, Aix Marseille Université, CNRS, LIS, France
 

AASP-P6.7: MUSICLDM: ENHANCING NOVELTY IN TEXT-TO-MUSIC GENERATION USING BEAT-SYNCHRONOUS MIXUP STRATEGIES
Ke Chen, University of California San Diego, United States of America; Yusong Wu, Université de Montréal, Canada; Haohe Liu, University of Surrey, United Kingdom of Great Britain and Northern Ireland; Marianna Nezhurina, LAION, Canada; Taylor Berg-Kirkpatrick, Shlomo Dubnov, University of California San Diego, United States of America
 

AASP-P6.8: A COMPARATIVE ANALYSIS OF POETRY READING AUDIO: SINGING, NARRATING, OR SOMEWHERE IN BETWEEN?
Kahyun Choi, Indiana University, United States of America; Minje Kim, University of Illinois at Urbana-Champaign, United States of America
 

AASP-P6.9: MIR-MLPOP: A MULTILINGUAL POP MUSIC DATASET WITH TIME-ALIGNED LYRICS AND AUDIO
Jun-You Wang, Chung-Che Wang, Chon-In Leong, Jyh-Shing Roger Jang, National Taiwan University, Taiwan
 

AASP-P6.10: GENERATING STEREOPHONIC MUSIC WITH SINGLE-STAGE LANGUAGE MODELS
Xingda Li, Fan Zhuo, Dan Luo, Jun Chen, Shiyin Kang, Skywork AI PTE. LTD, China; Zhiyong Wu, Shenzhen International Graduate School, Tsinghua University, China; Tao Jiang, Yang Li, Han Fang, Yahui Zhou, Skywork AI PTE. LTD, China
 

AASP-P6.11: STRING SOUND SYNTHESIZER ON GPU-ACCELERATED FINITE DIFFERENCE SCHEME
Jin Woo Lee, Min Jun Choi, Kyogu Lee, Seoul National University, Korea, Republic of
 

AASP-P6.12: MUSIC UNDERSTANDING LLAMA: ADVANCING TEXT-TO-MUSIC GENERATION WITH QUESTION ANSWERING AND CAPTIONING
Shansong Liu, Tencent, China; Atin Sakkeer Hussain, Chenshuo Sun, National University of Singapore, United Arab Emirates; Ying Shan, Tencent, United States of America