ON THE PERCEPTUAL RELEVANCE OF OBJECTIVE SOURCE SEPARATION MEASURES FOR SINGING VOICE SEPARATION

被引:0
|
作者
Gupta, Udit [1 ]
Moore, Elliot, II [1 ]
Lerch, Alexander [2 ]
机构
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Ctr Mus Technol, Atlanta, GA 30332 USA
来源
2015 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) | 2015年
关键词
Singing Voice Separation; Source Separation; Music Information Retrieval; MUSHRA;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Singing Voice Separation (SVS) is a task which uses audio source separation methods to isolate the vocal component from the background accompaniment for a song mix. This paper discusses the methods of evaluating SVS algorithms, and determines how the current state of the art measures correlate to human perception. A modified ITU-R BS. 1543 MUSHRA test is used to get the human perceptual ratings for the outputs of various SVS algorithms, which are correlated with widely used objective measures for source separation quality. The results show that while the objective measures provide a moderate correlation with perceived intelligibility and isolation, they may not adequately assess the overall perceptual quality.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] Singing Voice Separation Based on Deep Regression Neural Network
    Yang, Shuqian
    Zhang, Wei-Qiang
    2019 IEEE 19TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT 2019), 2019,
  • [22] Separation of singing voice from music accompaniment for monaural recordings
    Li, Yipeng
    Wang, DeLiang
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2007, 15 (04): : 1475 - 1487
  • [23] VOCAL ACTIVITY INFORMED SINGING VOICE SEPARATION WITH THE IKALA DATASET
    Chan, Tak-Shing
    Yeh, Tzu-Chun
    Fan, Zhe-Cheng
    Chen, Hung-Wei
    Sui, Li
    Yang, Yi-Hsuan
    Jang, Roger
    2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 718 - 722
  • [24] H-Semantics: A Hybrid Approach to Singing Voice Separation
    Sofianos, Stratis
    Ariyaeeinia, Aladdin
    Polfreman, Richard
    Sotudeh, Reza
    JOURNAL OF THE AUDIO ENGINEERING SOCIETY, 2012, 60 (10): : 831 - 841
  • [25] Informed Group-Sparse Representation for Singing Voice Separation
    Chan, Tak-Shing T.
    Yang, Yi-Hsuan
    IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (02) : 156 - 160
  • [26] Singing voice separation using mono-channel mask
    Ingale P.P.
    Nalbalwar S.L.
    International Journal of Speech Technology, 2018, 21 (2) : 309 - 318
  • [27] On strategies to exploit dependencies between singing voice alignment and separation
    Theo Nguyen
    Teytaut, Yann
    Roebel, Axel
    32ND EUROPEAN SIGNAL PROCESSING CONFERENCE, EUSIPCO 2024, 2024, : 366 - 370
  • [28] RPCA-DRNN technique for monaural singing voice separation
    Wen-Hsing Lai
    Siou-Lin Wang
    EURASIP Journal on Audio, Speech, and Music Processing, 2022
  • [29] SVSGAN: SINGING VOICE SEPARATION VIA GENERATIVE ADVERSARIAL NETWORK
    Fan, Zhe-Cheng
    Lai, Yen-Lin
    Jang, Jyh-Shing R.
    2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, : 726 - 730
  • [30] Neural Vocoder Feature Estimation for Dry Singing Voice Separation
    Im, Jaekwon
    Choi, Soonbeom
    Yong, Sangeon
    Nam, Juhan
    PROCEEDINGS OF 2022 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2022, : 809 - 814