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ORCIDGerhard Widmer
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- affiliation: Johannes Kepler University of Linz, Austria
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2020 – today
- 2023
[i96]Shreyan Chowdhury, Gerhard Widmer:
Decoding and Visualising Intended Emotion in an Expressive Piano Performance. CoRR abs/2303.01875 (2023)- [i95]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Low-Complexity Audio Embedding Extractors. CoRR abs/2303.01879 (2023) - 2022
- [j48]Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer
:
Differentiable Short-Term Models for Efficient Online Learning and Prediction in Monophonic Music. Trans. Int. Soc. Music. Inf. Retr. 5(1): 190 (2022) - [c198]Paul Primus, Gerhard Widmer:
Improving Natural-Language-Based Audio Retrieval with Transfer Learning and Audio & Text Augmentations. DCASE 2022 - [c197]Florian Schmid, Shahed Masoudian, Khaled Koutini, Gerhard Widmer:
Knowledge Distillation from Transformers for Low-Complexity Acoustic Scene Classification. DCASE 2022 - [c196]Paul Primus, Gerhard Widmer:
Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers. EUSIPCO 2022: 410-413 - [c195]Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, Gerhard Widmer:
Efficient Training of Audio Transformers with Patchout. INTERSPEECH 2022: 2753-2757 - [i94]Katharina Hoedt, Arthur Flexer, Gerhard Widmer:
Defending a Music Recommender Against Hubness-Based Adversarial Attacks. CoRR abs/2205.12032 (2022) - [i93]Carlos Cancino Chacón, Silvan David Peter, Emmanouil Karystinaios, Francesco Foscarin, Maarten Grachten, Gerhard Widmer:
Partitura: A Python Package for Symbolic Music Processing. CoRR abs/2206.01071 (2022) - [i92]Francesco Foscarin, Emmanouil Karystinaios, Silvan David Peter, Carlos Cancino Chacón, Maarten Grachten, Gerhard Widmer:
The match file format: Encoding Alignments between Scores and Performances. CoRR abs/2206.01104 (2022) - [i91]Paul Primus, Gerhard Widmer:
Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers. CoRR abs/2208.11402 (2022) - [i90]Paul Primus, Gerhard Widmer:
Improving Natural-Language-based Audio Retrieval with Transfer Learning and Audio & Text Augmentations. CoRR abs/2208.11460 (2022) - [i89]Francesco Foscarin, Katharina Hoedt, Verena Praher, Arthur Flexer, Gerhard Widmer:
Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier. CoRR abs/2208.12485 (2022) - [i88]Emmanouil Karystinaios, Gerhard Widmer:
Cadence Detection in Symbolic Classical Music using Graph Neural Networks. CoRR abs/2208.14819 (2022) - [i87]Florian Schmid, Khaled Koutini, Gerhard Widmer:
Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation. CoRR abs/2211.04772 (2022) - [i86]Khaled Koutini, Shahed Masoudian, Florian Schmid, Hamid Eghbal-zadeh, Jan Schlüter, Gerhard Widmer:
Learning General Audio Representations with Large-Scale Training of Patchout Audio Transformers. CoRR abs/2211.13956 (2022) - [i85]Lukás Samuel Marták, Rainer Kelz, Gerhard Widmer:
Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries. CoRR abs/2211.15439 (2022) - [i84]Lukás Samuel Marták, Rainer Kelz, Gerhard Widmer:
Differentiable Dictionary Search: Integrating Linear Mixing with Deep Non-Linear Modelling for Audio Source Separation. CoRR abs/2211.15524 (2022) - 2021
- [j47]Florian Henkel, Gerhard Widmer:
Real-Time Music Following in Score Sheet Images via Multi-Resolution Prediction. Frontiers Comput. Sci. 3: 718340 (2021) - [j46]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive Field Regularization Techniques for Audio Classification and Tagging With Deep Convolutional Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 29: 1987-2000 (2021) - [j45]Katharina Prinz, Arthur Flexer, Gerhard Widmer:
On End-to-End White-Box Adversarial Attacks in Music Information Retrieval. Trans. Int. Soc. Music. Inf. Retr. 4(1): 93 (2021) - [c194]Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer:
LEMONS: Listenable Explanations for Music recOmmeNder Systems. ECIR (2) 2021: 531-536 - [c193]Florian Henkel, Gerhard Widmer:
Multi-modal Conditional Bounding Box Regression for Music Score Following. EUSIPCO 2021: 356-360 - [c192]Charles Brazier, Gerhard Widmer:
Handling Structural Mismatches in Real-time Opera Tracking. EUSIPCO 2021: 366-370 - [c191]Luis Carvalho, Gerhard Widmer:
Exploiting Temporal Dependencies for Cross-modal Music Piece Identification. EUSIPCO 2021: 386-390 - [c190]Lukás Samuel Marták, Rainer Kelz, Gerhard Widmer:
Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries. EUSIPCO 2021: 441-445 - [c189]Gerhard Widmer:
Con Espressione! AI, Machine Learning, and Musical Expressivity. ICAART (1) 2021: 5 - [c188]Shreyan Chowdhury, Gerhard Widmer:
Towards Explaining Expressive Qualities in Piano Recordings: Transfer of Explanatory Features Via Acoustic Domain Adaptation. ICASSP 2021: 561-565 - [c187]Rainer Kelz, Gerhard Widmer:
Nonlinear Denoising, Linear Demixing. ICBINB@NeurIPS 2021: 54-58 - [c186]Charles Brazier, Gerhard Widmer:
On-Line Audio-to-Lyrics Alignment Based on a Reference Performance. ISMIR 2021: 66-73 - [c185]Shreyan Chowdhury, Gerhard Widmer:
On Perceived Emotion in Expressive Piano Performance: Further Experimental Evidence for the Relevance of Mid-level Perceptual Features. ISMIR 2021: 128-134 - [c184]Verena Praher, Katharina Prinz, Arthur Flexer, Gerhard Widmer:
On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples. ISMIR 2021: 531-538 - [i83]Shreyan Chowdhury, Gerhard Widmer:
Towards Explaining Expressive Qualities in Piano Recordings: Transfer of Explanatory Features via Acoustic Domain Adaptation. CoRR abs/2102.13479 (2021) - [i82]Florian Henkel, Gerhard Widmer:
Multi-modal Conditional Bounding Box Regression for Music Score Following. CoRR abs/2105.04309 (2021) - [i81]Charles Brazier, Gerhard Widmer:
Handling Structural Mismatches in Real-time Opera Tracking. CoRR abs/2105.08531 (2021) - [i80]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive Field Regularization Techniques for Audio Classification and Tagging with Deep Convolutional Neural Networks. CoRR abs/2105.12395 (2021) - [i79]Luis Carvalho, Gerhard Widmer:
Exploiting Temporal Dependencies for Cross-Modal Music Piece Identification. CoRR abs/2105.12536 (2021) - [i78]Shreyan Chowdhury, Verena Praher, Gerhard Widmer:
Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual Qualities. CoRR abs/2106.07787 (2021) - [i77]Khaled Koutini, Hamid Eghbal-zadeh, Florian Henkel, Jan Schlüter, Gerhard Widmer:
Over-Parameterization and Generalization in Audio Classification. CoRR abs/2107.08933 (2021) - [i76]Verena Praher, Katharina Prinz, Arthur Flexer, Gerhard Widmer:
On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples. CoRR abs/2107.09045 (2021) - [i75]Shreyan Chowdhury, Gerhard Widmer:
On Perceived Emotion in Expressive Piano Performance: Further Experimental Evidence for the Relevance of Mid-level Perceptual Features. CoRR abs/2107.13231 (2021) - [i74]Charles Brazier, Gerhard Widmer:
Improving Real-time Score Following in Opera by Combining Music with Lyrics Tracking. CoRR abs/2110.02592 (2021) - [i73]Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, Gerhard Widmer:
Efficient Training of Audio Transformers with Patchout. CoRR abs/2110.05069 (2021) - [i72]Florian Henkel, Stephanie Schwaiger, Gerhard Widmer:
Fully Automatic Page Turning on Real Scores. CoRR abs/2111.06643 (2021) - 2020
- [c183]Khaled Koutini, Florian Henkel, Hamid Eghbal-Zadeh, Gerhard Widmer:
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping. DCASE 2020: 86-90 - [c182]Paul Primus, Verena Haunschmid, Patrick Praher, Gerhard Widmer:
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples. DCASE 2020: 170-174 - [c181]Carlos Eduardo Cancino Chacón, Silvan Peter, Shreyan Chowdhury, Anna Aljanaki, Gerhard Widmer:
On the Characterization of Expressive Performance in Classical Music: First Results of the Con Espressione Game. ISMIR 2020: 613-620 - [c180]Florian Henkel, Rainer Kelz, Gerhard Widmer:
Learning to Read and Follow Music in Complete Score Sheet Images. ISMIR 2020: 780-787 - [c179]Hamid Eghbal-zadeh, Florian Henkel, Gerhard Widmer:
Context-Adaptive Reinforcement Learning using Unsupervised Learning of Context Variables. Preregister@NeurIPS 2020: 236-254 - [i71]Charles Brazier, Gerhard Widmer:
Towards Reliable Real-time Opera Tracking: Combining Alignment with Audio Event Detectors to Increase Robustness. CoRR abs/2006.11033 (2020) - [i70]David R. W. Sears, Gerhard Widmer:
Beneath (or beyond) the surface: Discovering voice-leading patterns with skip-grams. CoRR abs/2006.15399 (2020) - [i69]Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard Alois Moser, Gerhard Widmer:
On Data Augmentation and Adversarial Risk: An Empirical Analysis. CoRR abs/2007.02650 (2020) - [i68]Florian Henkel, Rainer Kelz, Gerhard Widmer:
Learning to Read and Follow Music in Complete Score Sheet Images. CoRR abs/2007.10736 (2020) - [i67]Khaled Koutini, Hamid Eghbal-Zadeh, Verena Haunschmid, Paul Primus, Shreyan Chowdhury, Gerhard Widmer:
Receptive-Field Regularized CNNs for Music Classification and Tagging. CoRR abs/2007.13503 (2020) - [i66]Verena Haunschmid, Ethan Manilow, Gerhard Widmer:
audioLIME: Listenable Explanations Using Source Separation. CoRR abs/2008.00582 (2020) - [i65]Carlos Eduardo Cancino Chacón, Silvan Peter, Shreyan Chowdhury, Anna Aljanaki, Gerhard Widmer:
On the Characterization of Expressive Performance in Classical Music: First Results of the Con Espressione Game. CoRR abs/2008.02194 (2020) - [i64]Katharina Prinz, Arthur Flexer, Gerhard Widmer:
The Impact of Label Noise on a Music Tagger. CoRR abs/2008.06273 (2020) - [i63]Verena Haunschmid, Ethan Manilow, Gerhard Widmer:
Towards Musically Meaningful Explanations Using Source Separation. CoRR abs/2009.02051 (2020) - [i62]Charles Brazier, Gerhard Widmer:
Addressing the Recitative Problem in Real-time Opera Tracking. CoRR abs/2010.11013 (2020) - [i61]Paul Primus, Verena Haunschmid, Patrick Praher, Gerhard Widmer:
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples. CoRR abs/2011.02949 (2020) - [i60]Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh, Gerhard Widmer:
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping. CoRR abs/2011.02955 (2020)
2010 – 2019
- 2019
- [j44]Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer:
Order, context and popularity bias in next-song recommendations. Int. J. Multim. Inf. Retr. 8(2): 101-113 (2019) - [j43]Hamid Eghbal-Zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Teresa Gerber, Eva Bozsaky, Peter F. Ambros, Inge M. Ambros, Gerhard Widmer, Bernhard Alois Moser:
DeepSNP: An End-to-End Deep Neural Network with Attention-Based Localization for Breakpoint Detection in Single-Nucleotide Polymorphism Array Genomic Data. J. Comput. Biol. 26(6): 572-596 (2019) - [j42]Meinard Müller, Andreas Arzt, Stefan Balke, Matthias Dorfer, Gerhard Widmer:
Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies. IEEE Signal Process. Mag. 36(1): 52-62 (2019) - [j41]Florian Henkel, Stefan Balke, Matthias Dorfer, Gerhard Widmer:
Score Following as a Multi-Modal Reinforcement Learning Problem. Trans. Int. Soc. Music. Inf. Retr. 2(1): 67-81 (2019) - [j40]Andreu Vall, Matthias Dorfer, Hamid Eghbal-zadeh, Markus Schedl, Keki Burjorjee, Gerhard Widmer:
Feature-combination hybrid recommender systems for automated music playlist continuation. User Model. User Adapt. Interact. 29(2): 527-572 (2019) - [c178]Hamid Eghbal-zadeh, Werner Zellinger, Gerhard Widmer:
Mixture Density Generative Adversarial Networks. CVPR 2019: 5820-5829 - [c177]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive-Field-Regularized CNN Variants for Acoustic Scene Classification. DCASE 2019: 124-128 - [c176]Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner, Khaled Koutini, Andreas Arzt, Gerhard Widmer:
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification. DCASE 2019: 204-208 - [c175]Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer:
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification. EUSIPCO 2019: 1-5 - [c174]Rainer Kelz, Sebastian Böck, Gerhard Widmer:
Deep Polyphonic ADSR Piano Note Transcription. ICASSP 2019: 246-250 - [c173]Stefan Balke, Matthias Dorfer, Luis Carvalho, Andreas Arzt, Gerhard Widmer:
Learning Soft-Attention Models for Tempo-invariant Audio-Sheet Music Retrieval. ISMIR 2019: 216-222 - [c172]Shreyan Chowdhury, Andreu Vall, Verena Haunschmid, Gerhard Widmer:
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features. ISMIR 2019: 237-243 - [c171]Rainer Kelz, Gerhard Widmer:
Towards Interpretable Polyphonic Transcription with Invertible Neural Networks. ISMIR 2019: 376-383 - [c170]Thassilo Gadermaier, Gerhard Widmer:
A Study of Annotation and Alignment Accuracy for Performance Comparison in Complex Orchestral Music. ISMIR 2019: 769-775 - [c169]Federico Simonetta, Carlos Eduardo Cancino Chacón, Stavros Ntalampiras, Gerhard Widmer:
A Convolutional Approach to Melody Line Identification in Symbolic Scores. ISMIR 2019: 924-931 - [c168]Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid, Hamid Eghbal-Zadeh, Gerhard Widmer:
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs. MediaEval 2019 - [i59]Rainer Kelz, Sebastian Böck, Gerhard Widmer:
Multitask Learning for Polyphonic Piano Transcription, a Case Study. CoRR abs/1902.04390 (2019) - [i58]Meinard Müller, Andreas Arzt, Stefan Balke, Matthias Dorfer, Gerhard Widmer:
Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies. CoRR abs/1902.04397 (2019) - [i57]Verena Haunschmid, Shreyan Chowdhury, Gerhard Widmer:
Two-level Explanations in Music Emotion Recognition. CoRR abs/1905.11760 (2019) - [i56]Zhengshan Shi, Carlos Cancino Chacón, Gerhard Widmer:
User Curated Shaping of Expressive Performances. CoRR abs/1906.06428 (2019) - [i55]Rainer Kelz, Sebastian Böck, Gerhard Widmer:
Deep Polyphonic ADSR Piano Note Transcription. CoRR abs/1906.09165 (2019) - [i54]Federico Simonetta, Carlos Eduardo Cancino Chacón, Stavros Ntalampiras, Gerhard Widmer:
A Convolutional Approach to Melody Line Identification in Symbolic Scores. CoRR abs/1906.10547 (2019) - [i53]Stefan Balke, Matthias Dorfer, Luis Carvalho, Andreas Arzt, Gerhard Widmer:
Learning Soft-Attention Models for Tempo-invariant Audio-Sheet Music Retrieval. CoRR abs/1906.10996 (2019) - [i52]Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer:
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification. CoRR abs/1907.01803 (2019) - [i51]Shreyan Chowdhury, Andreu Vall, Verena Haunschmid, Gerhard Widmer:
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features. CoRR abs/1907.03572 (2019) - [i50]Rainer Kelz, Gerhard Widmer:
Towards Interpretable Polyphonic Transcription with Invertible Neural Networks. CoRR abs/1909.01622 (2019) - [i49]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive-field-regularized CNN variants for acoustic scene classification. CoRR abs/1909.02859 (2019) - [i48]Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner, Khaled Koutini, Andreas Arzt, Gerhard Widmer:
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification. CoRR abs/1909.02869 (2019) - [i47]Florian Henkel, Rainer Kelz, Gerhard Widmer:
Audio-Conditioned U-Net for Position Estimation in Full Sheet Images. CoRR abs/1910.07254 (2019) - [i46]Thassilo Gadermaier, Gerhard Widmer:
A Study of Annotation and Alignment Accuracy for Performance Comparison in Complex Orchestral Music. CoRR abs/1910.07394 (2019) - [i45]Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid, Hamid Eghbal-zadeh, Gerhard Widmer:
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs. CoRR abs/1911.05833 (2019) - 2018
- [j39]Carlos Eduardo Cancino Chacón, Maarten Grachten, Werner Goebl, Gerhard Widmer:
Computational Models of Expressive Music Performance: A Comprehensive and Critical Review. Frontiers Digit. Humanit. 5: 25 (2018) - [j38]Matthias Dorfer, Jan Schlüter, Andreu Vall, Filip Korzeniowski, Gerhard Widmer:
End-to-end cross-modality retrieval with CCA projections and pairwise ranking loss. Int. J. Multim. Inf. Retr. 7(2): 117-128 (2018) - [j37]Bernhard Lehner, Jan Schlüter, Gerhard Widmer:
Online, Loudness-Invariant Vocal Detection in Mixed Music Signals. IEEE ACM Trans. Audio Speech Lang. Process. 26(8): 1369-1380 (2018) - [j36]Chih-Wei Wu, Christian Dittmar, Carl Southall, Richard Vogl, Gerhard Widmer, Jason Hockman, Meinard Müller, Alexander Lerch:
A Review of Automatic Drum Transcription. IEEE ACM Trans. Audio Speech Lang. Process. 26(9): 1457-1483 (2018) - [j35]Matthias Dorfer, Jan Hajic Jr., Andreas Arzt, Harald Frostel, Gerhard Widmer:
Learning Audio-Sheet Music Correspondences for Cross-Modal Retrieval and Piece Identification. Trans. Int. Soc. Music. Inf. Retr. 1(1): 22-31 (2018) - [c167]Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Iterative knowledge distillation in R-CNNs for weakly-labeled semi-supervised sound event detection. DCASE 2018: 173-177 - [c166]Matthias Dorfer, Gerhard Widmer:
Training general-purpose audio tagging networks with noisy labels and iterative self-verification. DCASE 2018: 178-182 - [c165]Filip Korzeniowski, Gerhard Widmer:
Automatic Chord Recognition with Higher-Order Harmonic Language Modelling. EUSIPCO 2018: 1900-1904 - [c164]Filip Korzeniowski, David R. W. Sears, Gerhard Widmer:
A Large-Scale Study of Language Models for Chord Prediction. ICASSP 2018: 91-95 - [c163]Rainer Kelz, Gerhard Widmer:
Investigating Label Noise Sensitivity of Convolutional Neural Networks for Fine Grained Audio Signal Labelling. ICASSP 2018: 2996-3000 - [c162]Filip Korzeniowski, Gerhard Widmer:
Improved Chord Recognition by Combining Duration and Harmonic Language Models. ISMIR 2018: 10-17 - [c161]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music based on Learned Interval Representations. ISMIR 2018: 26-33 - [c160]David R. W. Sears, Filip Korzeniowski, Gerhard Widmer:
Evaluating Language Models of Tonal Harmony. ISMIR 2018: 211-217 - [c159]Jan Hajic Jr., Matthias Dorfer, Gerhard Widmer, Pavel Pecina:
Towards Full-Pipeline Handwritten OMR with Musical Symbol Detection by U-Nets. ISMIR 2018: 225-232 - [c158]Filip Korzeniowski, Gerhard Widmer:
Genre-Agnostic Key Classification With Convolutional Neural Networks. ISMIR 2018: 264-270 - [c157]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Interval Representations from Polyphonic Music Sequences. ISMIR 2018: 661-668 - [c156]Matthias Dorfer, Florian Henkel, Gerhard Widmer:
Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game. ISMIR 2018: 784-791 - [c155]Andreu Vall, Gerhard Widmer:
Machine Learning Approaches to Hybrid Music Recommender Systems. ECML/PKDD (3) 2018: 639-642 - [c154]Andreu Vall, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
A hybrid approach to music playlist continuation based on playlist-song membership. SAC 2018: 1374-1382 - [i44]Filip Korzeniowski, David R. W. Sears, Gerhard Widmer:
A Large-Scale Study of Language Models for Chord Prediction. CoRR abs/1804.01849 (2018) - [i43]Andreu Vall, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
A Hybrid Approach to Music Playlist Continuation Based on Playlist-Song Membership. CoRR abs/1805.09557 (2018) - [i42]Rainer Kelz, Gerhard Widmer:
Investigating Label Noise Sensitivity of Convolutional Neural Networks for Fine Grained Audio Signal Labelling. CoRR abs/1805.10880 (2018) - [i41]Rainer Kelz, Gerhard Widmer:
Learning to Transcribe by Ear. CoRR abs/1805.11526 (2018) - [i40]Richard Vogl, Gerhard Widmer, Peter Knees:
Towards multi-instrument drum transcription. CoRR abs/1806.06676 (2018) - [i39]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio. CoRR abs/1806.08236 (2018) - [i38]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music Based on Learned Interval Representations. CoRR abs/1806.08686 (2018) - [i37]David R. W. Sears, Filip Korzeniowski, Gerhard Widmer:
Evaluating language models of tonal harmony. CoRR abs/1806.08724 (2018) - [i36]Hamid Eghbal-zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Khaled Koutini, Teresa Gerber, Eva Bozsaky, Peter F. Ambros, Inge M. Ambros, Gerhard Widmer, Bernhard Alois Moser:
Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data. CoRR abs/1806.08840 (2018) - [i35]Anna Aljanaki, Gerhard Widmer:
Modeling Majorness as a Perceptual Property in Music from Listener Ratings. CoRR abs/1806.10570 (2018) - [i34]