default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDCASE 2019, New York City, NY, USA
- Michael I. Mandel, Justin Salamon, Daniel P. W. Ellis:
Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events 2019 (DCASE 2019), New York University, NY, USA, October 2019. 2019, ISBN 978-0-578-59596-2 - Jakob Abeßer, Marco Götze, Tobias Clauß, Dominik Zapf, Christian Kühn, Hanna M. Lukashevich, Stephanie Kühnlenz, Stylianos I. Mimilakis:
Urban Noise Monitoring in the Stadtlärm Project - A Field Report. 1-4 - Sainath Adapa:
Urban Sound Tagging using Convolutional Neural Networks. 5-9 - Sharath Adavanne, Archontis Politis, Tuomas Virtanen:
A Multi-room Reverberant Dataset for Sound Event Localization and Detection. 10-14 - Sharath Adavanne, Haytham M. Fayek, Vladimir Tourbabin:
Sound Event Classification and Detection with Weakly Labeled Data. 15-19 - Sharath Adavanne, Archontis Politis, Tuomas Virtanen:
Localization, Detection and Tracking of Multiple Moving Sound Sources with a Convolutional Recurrent Neural Network. 20-24 - Osamu Akiyama, Junya Sato:
DCASE 2019 Task 2: Multitask Learning, Semi-supervised Learning and Model Ensemble with Noisy Data for Audio Tagging. 25-29 - Yin Cao, Qiuqiang Kong, Turab Iqbal, Fengyan An, Wenwu Wang, Mark D. Plumbley:
Polyphonic Sound Event Detection and Localization using a Two-Stage Strategy. 30-34 - Mark Cartwright, Ana Elisa Méndez Méndez, Jason Cramer, Vincent Lostanlen, Graham Dove, Ho-Hsiang Wu, Justin Salamon, Oded Nov, Juan Pablo Bello:
SONYC Urban Sound Tagging (SONYC-UST): A Multilabel Dataset from an Urban Acoustic Sensor Network. 35-39 - Teck Kai Chan, Cheng Siong Chin, Ye Li:
Non-Negative Matrix Factorization-Convolutional Neural Network (NMF-CNN) for Sound Event Detection. 40-44 - Janghoon Cho, Sungrack Yun, Hyoungwoo Park, Jungyun Eum, Kyuwoong Hwang:
Acoustic Scene Classification Based on a Large-margin Factorized CNN. 45-49 - Sotirios Panagiotis Chytas, Gerasimos Potamianos:
Hierarchical Detection of Sound Events and their Localization Using Convolutional Neural Networks with Adaptive Thresholds. 50-54 - Héctor A. Cordourier, Paulo Lopez-Meyer, Jonathan Huang, Juan A. del Hoyo Ontiveros, Hong Lu:
GCC-PHAT Cross-Correlation Audio Features for Simultaneous Sound Event Localization and Detection (SELD) on Multiple Rooms. 55-58 - Konstantinos Drossos, Shayan Gharib, Paul Magron, Tuomas Virtanen:
Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling. 59-63 - Janek Ebbers, Reinhold Häb-Umbach:
Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision. 64-68 - Eduardo Fonseca, Manoj Plakal, Frederic Font, Daniel P. W. Ellis, Xavier Serra:
Audio Tagging with Noisy Labels and Minimal Supervision. 69-73 - Ritwik Giri, Arvindh Krishnaswamy, Karim Helwani:
Robust Non-negative Block Sparse Coding for Acoustic Novelty Detection. 74-78 - Marc C. Green, Damian T. Murphy:
Sound Source Localisation in Ambisonic Audio Using Peak Clustering. 79-83 - François Grondin, Iwona Sobieraj, Mark D. Plumbley, James R. Glass:
Sound Event Localization and Detection Using CRNN on Pairs of Microphones. 84-88 - Kexin He, Yuhan Shen, Wei-Qiang Zhang:
Multiple Neural Networks with Ensemble Method for Audio Tagging with Noisy Labels and Minimal Supervision. 89-93 - Jonathan Huang, Hong Lu, Paulo Lopez-Meyer, Héctor A. Cordourier, Juan A. del Hoyo Ontiveros:
Acoustic Scene Classification Using Deep Learning-based Ensemble Averaging. 94-98 - Shota Ikawa, Kunio Kashino:
Neural Audio Captioning Based on Conditional Sequence-to-Sequence Model. 99-103 - Keisuke Imoto, Nobutaka Ono:
RU Multichannel Domestic Acoustic Scenes 2019: A Multichannel Dataset Recorded by Distributed Microphones with Various Properties. 104-108 - Tadanobu Inoue, Phongtharin Vinayavekhin, Shiqiang Wang, David Wood, Asim Munawar, Bong Jun Ko, Nancy Greco, Ryuki Tachibana:
Shuffling and Mixing Data Augmentation for Environmental Sound Classification. 109-113 - Jee-weon Jung, HeeSoo Heo, Hye-jin Shim, Ha-Jin Yu:
Distilling the Knowledge of Specialist Deep Neural Networks in Acoustic Scene Classification. 114-118 - Slawomir Kapka, Mateusz Lewandowski:
Sound Source Detection, Localization and Classification using Consecutive Ensemble of CRNN Models. 119-123 - Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer:
Receptive-Field-Regularized CNN Variants for Acoustic Scene Classification. 124-128 - Wootaek Lim:
SpecAugment for Sound Event Detection in Domestic Environments using Ensemble of Convolutional Recurrent Neural Networks. 129-133 - Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian:
Guided Learning Convolution System for DCASE 2019 Task 4. 134-138 - Samuel Lipping, Konstantinos Drossos, Tuomas Virtanen:
Crowdsourcing a Dataset of Audio Captions. 139-143 - Vincent Lostanlen, Kaitlin Palmer, Elly Knight, Christopher W. Clark, Holger Klinck, Andrew Farnsworth, Tina Wong, Jason Cramer, Juan Pablo Bello:
Long-distance Detection of Bioacoustic Events with Per-channel Energy Normalization. 144-148 - Rohith Mars, Pranay Pratik, Srikanth Nagisetty, Chongsoon Lim:
Acoustic Scene Classification from Binaural Signals using Convolutional Neural Networks. 149-153 - Luca Mazzon, Yuma Koizumi, Masahiro Yasuda, Noboru Harada:
First Order Ambisonics Domain Spatial Augmentation for DNN-based Direction of Arrival Estimation. 154-158 - Maarten Meire, Peter Karsmakers, Lode Vuegen:
The Impact of Missing Labels and Overlapping Sound Events on Multi-label Multi-instance Learning for Sound Event Classification. 159-163 - Annamaria Mesaros, Toni Heittola, Tuomas Virtanen:
Acoustic Scene Classification in DCASE 2019 Challenge: Closed and Open Set Classification and Data Mismatch Setups. 164-168 - Max Morrison, Bryan Pardo:
OtoMechanic: Auditory Automobile Diagnostics via Query-by-Example. 169-173 - Eric Nichols, Daniel Tompkins, Jianyu Fan:
Hierarchical Sound Event Classification. 248-252 - Arjun Pankajakshan, Helen L. Bear, Emmanouil Benetos:
Onsets, Activity, and Events: A Multi-task Approach for Polyphonic Sound Event Modelling. 174-178 - Sooyoung Park:
TrellisNet-Based Architecture for Sound Event Localization and Detection with Reassembly Learning. 179-183 - Hyoungwoo Park, Sungrack Yun, Jungyun Eum, Janghoon Cho, Kyuwoong Hwang:
Weakly Labeled Sound Event Detection using Tri-training and Adversarial Learning. 184-188 - Andrés Pérez-López, Eduardo Fonseca, Xavier Serra:
A Hybrid Parametric-Deep Learning Approach for Sound Event Localization and Detection. 189-193 - Fatemeh Pishdadian, Prem Seetharaman, Bongjun Kim, Bryan Pardo:
Classifying Non-speech Vocals: Deep vs Signal Processing Representations. 194-198 - Pranay Pratik, Wen Jie Jee, Srikanth Nagisetty, Rohith Mars, Chongsoon Lim:
Sound Event Localization and Detection using CRNN Architecture with Mixup for Model Generalization. 199-203 - 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. 204-208 - Harsh Purohit, Ryo Tanabe, Takeshi Ichige, Takashi Endo, Yuki Nikaido, Kaori Suefusa, Yohei Kawaguchi:
MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection. 209-213 - Rishabh Ranjan, Sathish Jayabalan, Thi Ngoc Tho Nguyen, Woon-Seng Gan:
Sound Event Detection and Direction of Arrival Estimation using Residual Net and Recurrent Neural Networks. 214-218 - Fatemeh Saki, Yinyi Guo, Cheng-Yu Hung, Lae-Hoon Kim, Manyu Deshpande, Sunkuk Moon, Eunjeong Koh, Erik Visser:
Open-set Evolving Acoustic Scene Classification System. 219-223 - Ziqiang Shi, Liu Liu, Huibin Lin, Rujie Liu, Anyan Shi:
HODGEPODGE: Sound Event Detection Based on Ensemble of Semi-Supervised Learning Methods. 224-228 - Arshdeep Singh, Padmanabhan Rajan, Arnav Bhavsar:
Deep Multi-view Features from Raw Audio for Acoustic Scene Classification. 229-233 - Shubhr Singh, Arjun Pankajakshan, Emmanouil Benetos:
Audio Tagging using Linear Noise Modelling Layer. 234-238 - Vinod Subramanian, Emmanouil Benetos, Mark B. Sandler:
Robustness of Adversarial Attacks in Sound Event Classification. 239-243 - Yui Sudo, Katsutoshi Itoyama, Kenji Nishida, Kazuhiro Nakadai:
Improvement of DOA Estimation by using Quaternion Output in Sound Event Localization and Detection. 244-247 - Nicolas Turpault, Romain Serizel, Justin Salamon, Ankit Parag Shah:
Sound Event Detection in Domestic Environments with Weakly Labeled Data and Soundscape Synthesis. 253-257 - Kevin Wilkinghoff, Frank Kurth:
Open-Set Acoustic Scene Classification with Deep Convolutional Autoencoders. 258-262 - Pablo Zinemanas, Pablo Cancela, Martín Rocamora:
MAVD: A Dataset for Sound Event Detection in Urban Environments. 263-267
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-11-11 23:03 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
