| Session A - Musical objects |
|---|
| When: Monday 2018-09-24 / Oral from 09:00 to 10:30 / Poster from 11:00 to 12:30 |
| Chair: Emmanouil Benetos |
(A-1) A Confidence Measure For Key Labelling
Roman B. Gebhardt, Michael Stein and Athanasios Lykartsis
|
(A-2) Improved Chord Recognition by Combining Duration and Harmonic Language Models
Filip Korzeniowski and Gerhard Widmer
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(A-3) Using musical relationships between chord labels in Automatic Chord Extraction tasks
Tristan Carsault, Jerome Nika and Philippe Esling
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(A-4) A Predictive Model for Music based on Learned Interval Representations
Stefan Lattner, Maarten Grachten and Gerhard Widmer
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(A-5) An End-to-end Framework for Audio-to-Score Music Transcription on Monophonic Excerpts
Miguel A. Román, Antonio Pertusa and Jorge Calvo-Zaragoza
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(A-6) Evaluating Automatic Polyphonic Music Transcription
Andrew McLeod and Mark Steedman
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(A-7) Onsets and Frames: Dual-Objective Piano Transcription
Curtis Hawthorne, Erich Elsen, Jialin Song, Adam Roberts, Ian Simon, Colin Raffel, Jesse Engel, Sageev Oore and Douglas Eck
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(A-8) Player Vs Transcriber: A Game Approach To Data Manipulation For Automatic Drum Transcription
Carl Southall, Ryan Stables and Jason Hockman
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(A-9) A Flexible Approach to Automated Harmonic Analysis: Multiple Annotations of Chorales by Bach and Prætorius
Nathaniel Condit-Schultz, Yaolong Ju and Ichiro Fujinaga
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(A-10) Evaluating a collection of Sound-Tracing Data of Melodic Phrases
Tejaswinee Kelkar, Udit Roy and Alexander Refsum Jensenius
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(A-11) Main Melody Estimation with Source-Filter NMF and CRNN
Dogac Basaran, Slim Essid and Geoffroy Peeters
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(A-12) Functional Harmony Recognition of Symbolic music data with Multi-task Recurrent Neural Networks
Tsung-Ping Chen and Li Su
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(A-13) A single-step approach to musical tempo estimation using a convolutional neural network
Hendrik Schreiber and Meinard Mueller
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(A-14) Analysis of Common Design Choices in Deep Learning Systems for Downbeat Tracking
Magdalena Fuentes, Brian McFee, Hélène C. Crayencour, Slim Essid and Juan Pablo Bello
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(A-15) Meter Detection and Alignment of MIDI Performance
Andrew McLeod and Mark Steedman
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(A-16) A Timbre-based Approach to Estimate Key Velocity from Polyphonic Piano Recordings
Dasaem Jeong, Taegyun Kwon and Juhan Nam
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(A-17) Timbre Discrimination for Brief Instrument Sounds
Francesco Bigoni and Sofia Dahl
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(A-18) Frame-level Instrument Recognition by Timbre and Pitch
Yun-Ning Hung and Yi-Hsuan Yang
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|
| Session B - Generation, visual |
|---|
| When: Monday 2018-09-24 / Oral from 14:30 to 16:00 / Poster from 16:30 to 18:00 |
| Chair: Anja Volk |
(B-1) Interactive Arrangement of Chords and Melodies Based on a Tree-Structured Generative Model
Hiroaki Tsushima, Eita Nakamura, Katsutoshi Itoyama and Kazuyoshi Yoshii
|
(B-2) A Generalized Parsing Framework for Generative Models of Harmonic Syntax
Daniel Harasim, Martin Rohrmeier and Timothy J. O'Donnell
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(B-3) An energy-based generative sequence model for testing sensory theories of Western harmony
Peter M. C. Harrison and Marcus T. Pearce
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(B-4) Automatic, Personalized, and Flexible Playlist Generation using Reinforcement Learning
Shun-Yao Shih and Heng-Yu Chi
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(B-5) Bridging audio analysis, perception and synthesis with perceptually-regularized variational timbre spaces
Philippe Esling, Axel Chemla--Romeu-Santos and Adrien Bitton
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(B-6) Conditioning Deep Generative Raw Audio Models for Structured Automatic Music
Rachel Manzelli, Vijay Thakkar, Ali Siahkamari and Brian Kulis
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(B-7) Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation
Hao-Wen Dong and Yi-Hsuan Yang
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(B-8) Cover Song Synthesis by Analogy
Christopher Tralie
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(B-9) Part-invariant Model for Music Generation and Harmonization
Yujia Yan, Ethan Lustig, Joseph VanderStel and Zhiyao Duan
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(B-10) Evaluating language models of tonal harmony
David Sears, Filip Korzeniowski and Gerhard Widmer
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(B-11) Skeleton plays piano: online generation of pianist body movements from MIDI performance
Bochen Li, Akira Maezawa and Zhiyao Duan
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(B-12) Towards Full-Pipeline Handwritten OMR with Musical Symbol Detection by U-Nets
Jan Hajič jr., Matthias Dorfer, Gerhard Widmer and Pavel Pecina
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(B-13) Searching Page-Images of Early Music Scanned with OMR: A Scalable Solution Using Minimal Absent Words
Tim Crawford, Golnaz Badkobeh and David Lewis
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(B-14) Optical Music Recognition in Mensural Notation with Region-based Convolutional Neural Networks
Alexander Pacha and Jorge Calvo-Zaragoza
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(B-15) Camera-PrIMuS: Neural End-to-End Optical Music Recognition on Realistic Monophonic Scores
Jorge Calvo-Zaragoza and David Rizo
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(B-16) Document Analysis of Music Score Images with Selectional Auto-Encoders
Francisco Castellanos, Jorge Calvo-Zaragoza, Gabriel Vigliensoni and Ichiro Fujinaga
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(B-17) Genre-Agnostic Key Classification With Convolutional Neural Networks
Filip Korzeniowski and Gerhard Widmer
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(B-18) Deep Watershed Detector for Music Object Recognition
Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber and Thilo Stadelmann
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|
| Session C - Source separation, symbolic, emotion |
|---|
| When: Tuesday 2018-09-25 / Oral from 09:00 to 10:30 / Poster: from 11:00 to 12:30 |
| Chair: Eric Humphrey |
(C-1) Deep neural networks with voice entry estimation heuristics for voice separation in symbolic music representations
Reinier de Valk and Tillman Weyde
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(C-2) Music Source Separation Using Stacked Hourglass Networks
Sungheon Park, Taehoon Kim, Kyogu Lee and Nojun Kwak
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(C-3) The Northwestern University Source Separation Library
Ethan Manilow, Prem Seetharaman and Bryan Pardo
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(C-4) Improving Bass Saliency Estimation using Transfer Learning and Label Propagation
Jakob Abeßer, Stefan Balke and Meinard Müller
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(C-5) Improving Peak-picking Using Multiple Time-step Loss Functions
Carl Southall, Ryan Stables and Jason Hockman
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(C-6) Zero-Mean Convolutions for Level-Invariant Singing Voice Detection
Jan Schlüter and Bernhard Lehner
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(C-7) Music Generation and Transformation with Moment Matching-Scattering Inverse Networks
Mathieu Andreux and Stéphane Mallat
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(C-8) Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation
Daniel Stoller, Sebastian Ewert and Simon Dixon
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(C-9) SE and SNL diagrams: Flexible data structures for MIR
Melissa R. McGuirl, Katherine M. Kinnaird, Claire Savard and Erin H. Bugbee
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(C-10) JSYMBOLIC 2.2: Extracting Features from Symbolic Music for use in Musicological and MIR Research
Cory McKay, Julie Cumming and Ichiro Fujinaga
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(C-11) Relevance of musical features for cadence detection
Louis Bigo, Laurent Feisthauer, Mathieu Giraud and Florence Levé
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(C-12) On the Relationships between Music-induced Emotion and Physiological Signals
Xiao Hu, Fanjie Li and Jeremy T. D. Ng
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(C-13) Music Mood Detection Based on Audio and Lyrics with Deep Neural Net
Rémi Delbouys, Romain Hennequin, Francesco Piccoli, Jimena Royo-Letelier and Manuel Moussallam
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(C-14) Identifying Emotions in Opera Singing: Implications of Adverse Acoustic Conditions
Emilia Parada-Cabaleiro, Maximilian Schmitt, Anton Batliner, Simone Hantke, Giovanni Costantini, Klaus Scherer and Bjoern Schuller
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(C-15) Musical Texture and Expressivity Features for Music Emotion Recognition
Renato Panda, Ricardo Malheiro and Rui Pedro Paiva
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(C-16) Shared generative representation of auditory concepts and EEG to reconstruct perceived and imagined music
André Ofner and Sebastian Stober
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(C-17) Exploring Musical Relations Using Association Rule Networks
Renan de Padua, Verônica Oliveira de Carvalho, Solange Rezende and Diego Furtado Silva
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| Session D - Corpora and voice |
|---|
| When: Tuesday 2018-09-25 / Oral: from 14:30pm to 16:00 / Poster: 16:30 to 18:00 |
| Chair: Xiao Hu |
(D-1) A Crowdsourced Experiment for Tempo Estimation of Electronic Dance Music
Hendrik Schreiber and Meinard Mueller
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(D-2) Computational Corpus Analysis: A Case Study on Jazz Solos
Christof Weiss, Stefan Balke, Jakob Abesser and Meinard Mueller
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(D-3) Controlled Vocabularies for Music Metadata
Pasquale Lisena, Konstantin Todorov, Cécile Cecconi, Françoise Leresche, Isabelle Canno, Frédéric Puyrenier, Martine Voisin, Thierry Le Meur and Raphaël Troncy
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(D-4) DALI: a large Dataset of synchronized Audio, LyrIcs and notes, automatically created using teacher-student machine learning paradigm
Gabriel Meseguer-Brocal, Alice Cohen-Hadria and Geoffroy Peeters
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(D-5) OpenMIC-2018: An open data-set for multiple instrument recognition
Eric Humphrey, Simon Durand and Brian McFee
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(D-6) From Labeled to Unlabeled Data – On the Data Challenge in Automatic Drum Transcription
Chih-Wei Wu and Alexander Lerch
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(D-7) GuitarSet: A Dataset for Guitar Transcription
Qingyang Xi, Rachel Bittner, Johan Pauwels, Xuzhou Ye and Juan Bello
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(D-8) Musical-Linguistic Annotations of Il Lauro Secco
Emilia Parada-Cabaleiro, Maximilian Schmitt, Anton Batliner and Bjoern Schuller
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(D-9) VocalSet: A Singing Voice Dataset
Julia Wilkins, Prem Seetharaman, Alison Wahl and Bryan Pardo
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(D-10) The NES Music Database: A multi-instrumental dataset with expressive performance attributes
Chris Donahue, Huanru Henry Mao and Julian McAuley
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(D-11) Audio-Aligned Jazz Harmony Dataset for Automatic Chord Transcription and Corpus-based Research
Vsevolod Eremenko, Emir Demirel, Baris Bozkurt and Xavier Serra
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(D-12) Methodologies for Creating Symbolic Corpora of Western Music Before 1600
Julie Cumming, Cory McKay, Jonathan Stuchbery and Ichiro Fujinaga
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(D-13) Precision of Sung Notes in Carnatic Music
Venkata Viraraghavan, Rangarajan Aravind and Hema Murthy
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(D-14) Revisiting Singing Voice Detection: A quantitative review and the future outlook
Kyungyun Lee, Keunwoo Choi and Juhan Nam
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(D-15) Vocals in Music Matter: the Relevance of Vocals in the Minds of Listeners
Andrew Demetriou, Andreas Jansson, Aparna Kumar and Rachel Bittner
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(D-16) Vocal melody extraction with semantic segmentation and audio-symbolic domain transfer learning
Wei Tsung Lu and Li Su
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(D-17) Empirically Weighting the Importance of Decision Factors for Singing Preference
Michael Barone, Karim Ibrahim, Chitralekha Gupta and Ye Wang
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|
| Session E - Timbre, tagging, similarity, patterns and alignment |
|---|
| When: Wednesday 2018-09-26 / Oral from 09:00 to 10:30 / Poster: from 11:00 to 12:30 |
| Chair: Bob Sturm |
(E-1) Analysis by classification: A comparative study of annotated and algorithmically extracted patterns in symbolic music data
Iris Yuping Ren, Anja Volk, Wouter Swierstra and Remco Veltkamp
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(E-2) Generalized Skipgrams for Pattern Discovery in Polyphonic Streams
Christoph Finkensiep, Markus Neuwirth and Martin Rohrmeier
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(E-3) Comparison of Audio Features for Recognition of Western and Ethnic Instruments in Polyphonic Mixtures
Igor Vatolkin and Günter Rudolph
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(E-4) Instrudive: A Music Visualization System Based on Automatically Recognized Instrumentation
Takumi Takahashi, Satoru Fukayama and Masataka Goto
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(E-5) Instrument Activity Detection in Polyphonic Music using Deep Neural Networks
Siddharth Gururani, Cameron Summers and Alexander Lerch
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(E-6) Jazz Solo Instrument Classification with Convolutional Neural Networks, Source Separation, and Transfer Learning
Juan S. Gómez, Jakob Abeßer and Estefanía Cano
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(E-7) Aligned sub-Hierarchies: a structure-based approach to the cover song task
Katherine M. Kinnaird
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(E-8) Audio-to-Score Alignment using Transposition-invariant Features
Andreas Arzt and Stefan Lattner
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(E-9) Semi-supervised lyrics and solo-singing alignment
Chitralekha Gupta, Rong Tong, Haizhou Li and Ye Wang
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(E-10) Concert Stitch: Organization and Synchronization of Crowd Sourced Recordings
Vinod Subramanian and Alexander Lerch
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(E-11) A data-driven approach to mid-level perceptual musical feature modeling
Anna Aljanaki and Mohammad Soleymani
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(E-12) Disambiguating Music Artists at Scale with Audio Metric Learning
Jimena Royo-Letelier, Romain Hennequin, Viet-Anh Tran and Manuel Moussallam
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(E-13) Driftin’ down the scale: Dynamic time warping in the presence of pitch drift and transpositions
Simon Waloschek and Aristotelis Hadjakos
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(E-14) End-to-end Learning for Music Audio Tagging at Scale
Jordi Pons, Oriol Nieto, Matthew Prockup, Erik M. Schmidt, Andreas F. Ehmann and Xavier Serra
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(E-15) Audio based disambiguation of music genre tags
Romain Hennequin, Jimena Royo-Letelier and Manuel Moussallam
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(E-16) Learning Domain-Adaptive Latent Representations of Music Signals Using Variational Autoencoders
Yin-Jyun Luo and Li Su
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(E-17) Learning Interval Representations from Polyphonic Music Sequences
Stefan Lattner, Maarten Grachten and Gerhard Widmer
|
|
| Session F - Machine and human learning of music |
|---|
| When: Wednesday 2018-09-26 / Oral from 14:30 to 16:00 / Poster: 16:30 to 18:00 |
| Chair: Emilia Gomez |
(F-1) Influences on the Social Practices Surrounding Commercial Music Services: A Model for Rich Interactions
Louis Spinelli, Josephine Lau, Liz Pritchard and Jin Ha Lee
|
(F-2) Investigating Cross-Country Relationship between Users’ Social Ties and Music Mainstreaminess
Christine Bauer and Markus Schedl
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(F-3) Listener Anonymizer: Camouflaging Play Logs to Preserve User’s Demographic Anonymity
Kosetsu Tsukuda, Satoru Fukayama and Masataka Goto
|
(F-4) On the Impact of Music on Decision Making in Cooperative Tasks
Elad Liebman, Corey N. White and Peter Stone
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(F-5) VenueRank: Identifying Venues that Contribute to Artist Popularity
Emmanouil Krasanakis, Emmanouil Schinas, Symeon Papadopoulos, Yiannis Kompatsiaris and Pericles Mitkas
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(F-6) The Many Faces of Users: Modeling Musical Preference
Eva Zangerle and Martin Pichl
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(F-7) Representation Learning of Music Using Artist Labels
Jiyoung Park, Jongpil Lee, Jangyeon Park, Jung-Woo Ha and Juhan Nam
|
(F-8) StructureNet: Inducing Structure in Generated Melodies
Gabriele Medeot, Srikanth Cherla, Katerina Kosta, Matt McVicar, Samer Abdallah, Marco Selvi, Ed Newton-Rex and Kevin Webster
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(F-9) Summarizing and Comparing Music Data and Its Application on Cover Song Identification
Diego Furtado Silva, Felipe Falcão and Nazareno Andrade
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(F-10) Transferring the Style of Homophonic Music Using Recurrent Neural Networks and Autoregressive Model
Wei Tsung Lu and Li Su
|
(F-11) MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer
Gino Brunner, Andres Konrad, Yuyi Wang and Roger Wattenhofer
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(F-12) Understanding a Deep Machine Listening Model Through Feature Inversion
Saumitra Mishra, Bob L. Sturm and Simon Dixon
|
(F-13) Comparing RNN Parameters for Melodic Similarity
Tian Cheng, Satoru Fukayama and Masataka Goto
|
(F-14) Visualization of audio data using stacked graphs
Mathieu Lagrange, Mathias Rossignol and Grégoire Lafay
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(F-15) Two web applications for exploring melodic patterns in jazz solos
Klaus Frieler, Frank Höger, Martin Pfleiderer and Simon Dixon
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(F-16) Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game
Matthias Dorfer, Florian Henkel and Gerhard Widmer
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(F-17) Matrix Co-Factorization for Cold-Start Recommendation
Olivier Gouvert, Thomas Oberlin and Cédric Févotte
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