AUD-P1: Deep Learning for Audio Classification |
| Session Type: Poster |
| Time: Tuesday, 5 May, 11:30 - 13:30 |
| Location: On-Demand |
| Virtual Session: View on Virtual Platform |
| Session Chair: Nobutaka Ito, NTT |
| AUD-P1.1: ANOMALOUS SOUND DETECTION BASED ON INTERPOLATION DEEP NEURAL NETWORK |
| Kaori Suefusa; Hitachi, Ltd. |
| Tomoya Nishida; University of Tokyo |
| Purohit Harsh; Hitachi, Ltd. |
| Ryo Tanabe; Hitachi, Ltd. |
| Takashi Endo; Hitachi, Ltd. |
| Yohei Kawaguchi; Hitachi, Ltd. |
| AUD-P1.2: A-CRNN: A DOMAIN ADAPTATION MODEL FOR SOUND EVENT DETECTION |
| Wei Wei; National University of Singapore |
| Hongning Zhu; Fudan University |
| Emmanouil Benetos; Queen Mary University of London |
| Ye Wang; National University of Singapore |
| AUD-P1.3: SPIDERNET: ATTENTION NETWORK FOR ONE-SHOT ANOMALY DETECTION IN SOUNDS |
| Yuma Koizumi; NTT Corporation |
| Masahiro Yasuda; NTT Corporation |
| Shin Murata; NTT Corporation |
| Shoichiro Saito; NTT Corporation |
| Hisashi Uematsu; NTT Corporation |
| Noboru Harada; NTT Corporation |
| AUD-P1.4: SOUND EVENT DETECTION VIA DILATED CONVOLUTIONAL RECURRENT NEURAL NETWORKS |
| Yanxiong Li; South China University of Technology |
| Mingle Liu; South China University of Technology |
| Konstantinos Drossos; Tampere University |
| Tuomas Virtanen; Tampere University |
| AUD-P1.5: A DEEP NEURAL NETWORK-DRIVEN FEATURE LEARNING METHOD FOR POLYPHONIC ACOUSTIC EVENT DETECTION FROM REAL-LIFE RECORDINGS |
| Manjunath Mulimani; Manipal Institute of Technology Manipal |
| Akash B Kademani; Symbiosis Institute of Technology |
| Shashidhar G Koolagudi; National Institute of Technology Karnataka |
| AUD-P1.6: WEAKLY LABELLED AUDIO TAGGING VIA CONVOLUTIONAL NETWORKS WITH SPATIAL AND CHANNEL-WISE ATTENTION |
| Sixin Hong; Peking University |
| Yuexian Zou; Peking University |
| Wenwu Wang; University of Surrey |
| Meng Cao; Peking University |
| AUD-P1.7: A STUDY ON THE TRANSFERABILITY OF ADVERSARIAL ATTACKS IN SOUND EVENT CLASSIFICATION |
| Vinod Subramanian; Queen Mary University of London |
| Arjun Pankajakshan; Queen Mary University of London |
| Emmanouil Benetos; Queen Mary University of London |
| Ning Xu; ROLI Ltd. |
| SKoT McDonald; ROLI Ltd. |
| Mark Sandler; Queen Mary University of London |
| AUD-P1.8: PROPELLER NOISE DETECTION WITH DEEP LEARNING |
| Thomas Mahiout; Thales |
| Lionel Fillatre; UCA |
| Laurent Deruaz-Pepin; Thales |
| AUD-P1.9: DURATION ROBUST WEAKLY SUPERVISED SOUND EVENT DETECTION |
| Heinrich Dinkel; Shanghai Jiao Tong University |
| Kai Yu; Shanghai Jiao Tong University |
| AUD-P1.10: A COMPARISON OF POOLING METHODS ON LSTM MODELS FOR RARE ACOUSTIC EVENT CLASSIFICATION |
| Chieh-Chi Kao; Amazon, Inc. |
| Ming Sun; Amazon, Inc. |
| Weiran Wang; Salesforce Research |
| Chao Wang; Amazon, Inc. |
| AUD-P1.11: AN ONTOLOGY-AWARE FRAMEWORK FOR AUDIO EVENT CLASSIFICATION |
| Yiwei Sun; Pennsylvania State University |
| Shabnam Ghaffarzadegan; Bosch Research and Technology Center |
| AUD-P1.12: TASK-AWARE MEAN TEACHER METHOD FOR LARGE SCALE WEAKLY LABELED SEMI-SUPERVISED SOUND EVENT DETECTION |
| Jie Yan; University of Science and Technology of China |
| Yan Song; University of Science and Technology of China |
| Li-Rong Dai; University of Science and Technology of China |
| Ian McLoughlin; University of Kent |