Abstract is missing.
- Sound Event Detection in Multichannel Audio Using Spatial and Harmonic FeaturesSharath Adavanne, Giambattista Parascandolo, Pasi Pertilä, Toni Heittola, Tuomas Virtanen. 6-10 [doi]
- Acoustic Scene Classification Using Parallel Combination of LSTM and CNNSoo Hyun Bae, In Kyu Choi, Nam Soo Kim. 11-15 [doi]
- DNN-Based Sound Event Detection with Exemplar-Based Approach for Noise ReductionIn Kyu Choi, Kisoo Kwon, Soo Hyun Bae, Nam Soo Kim. 16-19 [doi]
- Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life RecordingBenjamin Elizalde, Anurag Kumar 0003, Ankit Shah 0001, Rohan Badlani, Emmanuel Vincent 0001, Bhiksha Raj, Ian R. Lane. 20-24 [doi]
- Improved Dictionary Selection and Detection Schemes in Sparse-CNMF-Based Overlapping Acoustic Event DetectionPanagiotis Giannoulis, Gerasimos Potamianos, Petros Maragos, Athanasios Katsamanis. 25-29 [doi]
- Synthetic Sound Event Detection based on MFCCJuana M. Gutiérrez-Arriola, Rubén Fraile, Alexander Camacho, Thibaut Durand, Jaime L. Jarrín, Shirley R. Mendoza. 30-34 [doi]
- Bidirectional LSTM-HMM Hybrid System for Polyphonic Sound Event DetectionTomoki Hayashi, Shinji Watanabe 0001, Tomoki Toda, Takaaki Hori, Jonathan Le Roux, Kazuya Takeda. 35-39 [doi]
- Estimating Traffic Noise Levels Using Acoustic Monitoring a Preliminary StudyJean-Remy Gloaguen, Arnaud Can, Mathieu Lagrange, Jean-François Petiot. 40-44 [doi]
- Acoustic Event Detection Method Using Semi-Supervised Non-Negative Matrix Factorization with Mixtures of Local DictionariesTatsuya Komatsu, Takahiro Toizumi, Reishi Kondo, Yuzo Senda. 45-49 [doi]
- Deep Neural Network Baseline for DCASE Challenge 2016Qiuqiang Kong, Iwona Sobieraj, Wenwu Wang, Mark D. Plumbley. 50-54 [doi]
- Bag-of-Features Acoustic Event Detection for Sensor NetworksJulian Kürby, Rene Grzeszick, Axel Plinge, Gernot A. Fink. 55-59 [doi]
- CQT-based Convolutional Neural Networks for Audio Scene ClassificationThomas Lidy, Alexander Schindler. 60-64 [doi]
- Pairwise Decomposition with Deep Neural Networks and Multiscale Kernel Subspace Learning for Acoustic Scene ClassificationErik Marchi, Dario Tonelli, Xinzhou Xu, Fabien Ringeval, Jun Deng, Stefano Squartini, Björn W. Schuller. 65-69 [doi]
- Acoustic Scene Classification using Time-Delay Neural Networks and Amplitude Modulation Filter Bank FeaturesNiko Moritz, Jens Schröder, Stefan Goetze, Jörn Anemüller, Birger Kollmeier. 70-74 [doi]
- A Real-Time Environmental Sound Recognition System for the Android OSAngelos Pillos, Khalid Alghamidi, Noura Alzamel, Veselin Pavlov, Swetha Machanavajhala. 75-79 [doi]
- Performance comparison of GMM, HMM and DNN based approaches for acoustic event detection within Task 3 of the DCASE 2016 challengeJens Schröder, Jörn Anemüller, Stefan Goetze. 80-84 [doi]
- Acoustic Scene Classification: An evaluation of an extremely compact feature representationGustavo Sena Mafra, Ngoc Q. K. Duong, Alexey Ozerov, Patrick Pérez. 85-89 [doi]
- Coupled Sparse NMF vs. Random Forest Classification for Real Life Acoustic Event DetectionIwona Sobieraj, Mark D. Plumbley. 90-94 [doi]
- DCASE 2016 Acoustic Scene Classification Using Convolutional Neural NetworksMichele Valenti, Aleksandr Diment, Giambattista Parascandolo, Stefano Squartini, Tuomas Virtanen. 95-99 [doi]
- ABROA: Audio-Based Room-Occupancy Analysis Using Gaussian Mixtures and Hidden Markov ModelsRafael Valle. 100-104 [doi]
- Fully DNN-Based Multi-Label Regression for Audio TaggingYong Xu 0004, Qiang Huang 0007, Wenwu Wang, Philip J. B. Jackson, Mark D. Plumbley. 105-109 [doi]
- Hierarchical Learning for DNN-Based Acoustic Scene ClassificationYong Xu 0004, Qiang Huang 0007, Wenwu Wang, Mark D. Plumbley. 110-114 [doi]
- Gated Recurrent Networks applied to Acoustic Scene ClassificationMatthias Zöhrer, Franz Pernkopf. 115-119 [doi]