ISMIR
Member since:
2020-11-02
Last seen:
2020-12-14
User details
Name:
International Society for Music Information Retrieval
Website:
https://ismir.net/
About me:
The International Society for Music Information Retrieval (ISMIR) is a non-profit organisation which, among other things, oversees the organisation of the ISMIR Conference. The ISMIR conference is held annually and is the worlds leading research forum on processing, searching, organising and accessing music-related data.
Papertalks of ISMIR
11/10/2020
User Insights on Diversity in Music Recommendation Lists
Kyle Robinson, Dan Brown, Markus Schedl
Keywords Paper
Human-centered MIR, User-centered evaluation, Applications, Music recommendation and playlist generation, Evaluation, datasets, and reproducibility, Evaluation metrics, Human-computer interaction and interfaces, Personalization
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4:11
11/10/2020
From Music Ontology Towards Ethno-Music-Ontology
Polina Proutskova, Anja Volk, Peyman Heidarian, Gyorgy Fazekas
Keywords Paper
MIR fundamentals and methodology, Metadata, tags, linked data, and semantic web, Applications, Digital libraries and archives, Domain knowledge, Representations of music, Evaluation, datasets, and reproducibility, Novel datasets and use cases, Philosophical and ethical discussions, Philosophical and methodological foundations
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4:12
11/10/2020
A Combination of Local Approaches for Hierarchical Music Genre Classification
Antonio R. Parmezan, Diego Furtado Silva, Gustavo Batista
Keywords Paper
MIR tasks, Automatic classification, Domain knowledge, Machine learning/Artificial intelligence for music, MIR fundamentals and methodology, Music signal processing, Musical features and properties, Musical style and genre
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4:30
11/10/2020
Modeling Music and Code Knowledge to Support a Co-creative AI Agent for Education
Jason Smith, Erin Truesdell, Jason Freeman and
Keywords Paper
Applications, Music training and education, Domain knowledge, Representations of music, Human-centered MIR, User behavior analysis and mining, user modeling, MIR fundamentals and methodology, Multimodality, Symbolic music processing, Musical features and properties, Structure, segmentation, and form
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0
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4:02
11/10/2020
Multitask Learning for Instrument Activation Aware Music Source Separation
Yun-Ning Hung, Alexander Lerch
Keywords Paper
MIR tasks, Sound source separation, Domain knowledge, Machine learning/Artificial intelligence for music, Evaluation, datasets, and reproducibility, Novel datasets and use cases, Musical features and properties, Timbre, instrumentation, and voice
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4:06
11/10/2020
The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-composed Music Through Quantitative Measures
Shih-Lun Wu, Yi-Hsuan Yang
Keywords Paper
Evaluation, datasets, and reproducibility, Evaluation metrics, Applications, Music composition, performance, and production, Domain knowledge, Machine learning/Artificial intelligence for music
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0
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4:20
11/10/2020
Polyphonic Piano Transcription Using Autoregressive Multi-state Note Model
Taegyun Kwon, Dasaem Jeong, Juhan Nam
Keywords Paper
MIR tasks, Music transcription and annotation, Applications, Music composition, performance, and production, Music retrieval systems, MIR fundamentals and methodology, Music signal processing
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4:11
11/10/2020
Exact, Parallelizable Dynamic Time Warping Alignment with Linear Memory
Christopher J Tralie, Elizabeth Dempsey
Keywords Paper
MIR tasks, Alignment, synchronization, and score following, Applications, Music retrieval systems, Evaluation, datasets, and reproducibility, Evaluation metrics
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0
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4:09
11/10/2020
Automatic Composition of Guitar Tabs by Transformers and Groove Modeling
Yu-Hua Chen, Yu-Siang Huang, Wen-Yi Hsiao, Yi-Hsuan Yang
Keywords Paper
Applications, Music composition, performance, and production, Domain knowledge, Machine learning/Artificial intelligence for music, Representations of music, MIR fundamentals and methodology, Symbolic music processing, MIR tasks, Music synthesis and transformation, Musical features and properties, Rhythm, beat, tempo
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0
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0
4:33
11/10/2020
A Computational Analysis of Real-world DJ Mixes Using Mix-To-Track Subsequence Alignment
Taejun Kim, Minsuk Choi, Evan Sacks and
Keywords Paper
Applications, Music composition, performance, and production, Evaluation, datasets, and reproducibility, Novel datasets and use cases, MIR tasks, Alignment, synchronization, and score following, Musical features and properties, Structure, segmentation, and form
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3:31
11/10/2020
Explaining Perceived Emotion Predictions in Music: an Attentive Approach
Sanga Chaki, Pranjal Doshi, Sourangshu Bhattacharya, Prof. Priyadarshi Patnaik
Keywords Paper
Musical features and properties, Musical affect, emotion, and mood, Applications, Music recommendation and playlist generation, Music retrieval systems, Domain knowledge, Machine learning/Artificial intelligence for music, MIR tasks, Automatic classification, Pattern matching and detection
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3:15
11/10/2020
Bistate Reduction and Comparison of Drum Patterns
Olivier Lartillot, Fred Bruford
Keywords Paper
Musical features and properties, Rhythm, beat, tempo, Domain knowledge, Computational music theory and musicology, Representations of music, MIR fundamentals and methodology, Symbolic music processing, MIR tasks, Similarity metrics
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0
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4:09
11/10/2020
Pandemics, Music, and Collective Sentiment: Evidence from the Outbreak of COVID-19
Meijun Liu, Eva Zangerle, Xiao Hu and
Keywords Paper
Applications, Music retrieval systems, Music and health, well-being, and therapy, Music recommendation and playlist generation, Musical features and properties, Musical affect, emotion, and mood
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0
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4:26
11/10/2020
Score-informed Networks for Music Performance Assessment
Jiawen Huang, Yun-Ning Hung, Ashis Pati and
Keywords Paper
Musical features and properties, Expression and performative aspects of music, Applications, Music training and education, Domain knowledge, Machine learning/Artificial intelligence for music, MIR fundamentals and methodology, Multimodality
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4:08
11/10/2020
The Multiple Voices of Musical Emotions: Source Separation for Improving Music Emotion Recognition Models and Their Interpretability
Jacopo de Berardinis, Angelo Cangelosi, Eduardo Coutinho
Keywords Paper
Musical features and properties, Musical affect, emotion, and mood, Domain knowledge, Machine learning/Artificial intelligence for music, MIR tasks, Sound source separation
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0
0
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4:00
11/10/2020
Hierarchical Timbre-painting and Articulation Generation
Michael M Michelashvili, Lior Wolf
Keywords Paper
Domain knowledge, Machine learning/Artificial intelligence for music, Representations of music, MIR fundamentals and methodology, Music signal processing, MIR tasks, Music synthesis and transformation
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0
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0
4:04
11/10/2020
Semi-supervised Learning Using Teacher-student Models for Vocal Melody Extraction
Sangeun Kum, Jing-Hua Lin, Li Su, Juhan Nam
Keywords Paper
Musical features and properties, Melody and motives, Evaluation, datasets, and reproducibility, Novel datasets and use cases, MIR tasks, Music transcription and annotation
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0
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0
4:20
11/10/2020
Automatic Rank-ordering of Singing Vocals with Twin-neural Network
Chitralekha Gupta, Lin Huang, Haizhou Li
Keywords Paper
Domain knowledge, Machine learning/Artificial intelligence for music, Applications, Music training and education, Evaluation, datasets, and reproducibility, Evaluation methodology, MIR fundamentals and methodology, Music signal processing, MIR tasks, Similarity metrics, Musical features and properties, Timbre, instrumentation, and voice
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0
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4:07
11/10/2020
The MIDI Degradation Toolkit: Symbolic Music Augmentation and Correction
Andrew McLeod, James Owers, Kazuyoshi Yoshii
Keywords Paper
Evaluation, datasets, and reproducibility, Novel datasets and use cases, MIR fundamentals and methodology, Symbolic music processing, MIR tasks, Music transcription and annotation
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0
0
0
4:07
11/10/2020
Muspy: a Toolkit for Symbolic Music Generation
Hao-Wen Dong, Ke Chen, Julian McAuley, Taylor Berg-Kirkpatrick
Keywords Paper
MIR fundamentals and methodology, Symbolic music processing, Applications, Music composition, performance, and production, Domain knowledge, Machine learning/Artificial intelligence for music, Representations of music, Evaluation, datasets, and reproducibility, Evaluation metrics, Reproducibility
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4:06
11/10/2020
"Butter Lyrics Over Hominy Grit": Comparing Audio and Psychology-based Text Features in MIR Tasks
Jaehun Kim, Andrew M. Demetriou, Sandy Manolios and
Keywords Paper
MIR fundamentals and methodology, Lyrics and other textual data, web mining, and natural language , Applications, Music recommendation and playlist generation, Domain knowledge, Machine learning/Artificial intelligence for music, Evaluation, datasets, and reproducibility, MIR tasks, Automatic classification
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3:55
11/10/2020
Learning Interpretable Representation for Controllable Polyphonic Music Generation
Ziyu Wang, Dingsu Wang, Yixiao Zhang, Gus Xia
Keywords Paper
Applications, Music composition, performance, and production, Domain knowledge, Machine learning/Artificial intelligence for music, Representations of music, MIR fundamentals and methodology, Symbolic music processing
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0
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4:07
11/10/2020
PIANOTREE VAE: Structured Representation Learning for Polyphonic Music
Ziyu Wang, Yiyi Zhang, Yixiao Zhang and
Keywords Paper
Applications, Music composition, performance, and production, Domain knowledge, Machine learning/Artificial intelligence for music, Representations of music, MIR fundamentals and methodology, Symbolic music processing
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4:08
11/10/2020
Towards Multimodal MIR: Predicting Individual Differences from Music-induced Movement
Yudhik Agrawal, Samyak Jain, Emily Carlson and
Keywords Paper
Human-centered MIR, User behavior analysis and mining, user modeling, Domain knowledge, Machine learning/Artificial intelligence for music, Human-computer interaction and interfaces, Personalization, MIR fundamentals and methodology, Multimodality
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4:05
11/10/2020
Asap: a Dataset of Aligned Scores and Performances for Piano Transcription
Francesco Foscarin, Andrew McLeod, Philippe Rigaux and
Keywords Paper
Evaluation, datasets, and reproducibility, Novel datasets and use cases, Annotation protocols, MIR tasks, Music transcription and annotation
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3:27
11/10/2020
Music Sketchnet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm
Ke Chen, Cheng-i Wang, Taylor Berg-Kirkpatrick, Shlomo Dubnov
Keywords Paper
Domain knowledge, Machine learning/Artificial intelligence for music, Applications, Music composition, performance, and production, Representations of music, Human-centered MIR, Human-computer interaction and interfaces, Musical features and properties, Melody and motives, Rhythm, beat, tempo
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4:10
11/10/2020
Female Artist Representation in Music Streaming
Avriel C Epps-Darling, Henriette Cramer, Romain Takeo Bouyer
Keywords Paper
Philosophical and ethical discussions, Ethical issues related to designing and implementing MIR to, Applications, Music recommendation and playlist generation, Human-centered MIR, Human-computer interaction and interfaces, User behavior analysis and mining, user modeling, MIR fundamentals and methodology, Metadata, tags, linked data, and semantic web
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4:06
11/10/2020
Sesquialtera in the Colombian Bambuco: Perception and Estimation of Beat and Meter
Estefania Cano, Fernando Mora Ángel, Gustavo Adolfo López Gil and
Keywords Paper
Domain knowledge, Computational music theory and musicology, Applications, Digital libraries and archives, Evaluation, datasets, and reproducibility, Novel datasets and use cases, Musical features and properties, Rhythm, beat, tempo
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4:08
11/10/2020
Joint Analysis of Mode and Playing Technique in Guqin Performance with Machine Learning
Yu-Fen Huang, Jeng-I Liang, I-CHIEH WEI, Li Su
Keywords Paper
Domain knowledge, Computational music theory and musicology, MIR tasks, Automatic classification, Musical features and properties, Expression and performative aspects of music
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4:09
11/10/2020
Score Following with Hidden Tempo Using a Switching State-space Model
Yucong Jiang
Keywords Paper
MIR tasks, Alignment, synchronization, and score following, Domain knowledge, Machine learning/Artificial intelligence for music, MIR fundamentals and methodology, Music signal processing
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4:23
