5 papers
Weakly supervised CRNN system for sound event detection with large-scale unlabeled in-domain data
Dezhi Wang, Lilun Zhang, Changchun Bao +3
Sound event detection (SED) is typically posed as a supervised learning problem requiring training data with strong temporal labels of sound events. However, the production of data…
General audio tagging with ensembling convolutional neural network and statistical features
Kele Xu, Boqing Zhu, Qiuqiang Kong +4
Audio tagging aims to infer descriptive labels from audio clips. Audio tagging is challenging due to the limited size of data and noisy labels. In this paper, we describe our solut…
Sample Mixed-Based Data Augmentation for Domestic Audio Tagging
Shengyun Wei, Kele Xu, Dezhi Wang +3
Audio tagging has attracted increasing attention since last decade and has various potential applications in many fields. The objective of audio tagging is to predict the labels of…
Environmental Sound Classification Based on Multi-temporal Resolution Convolutional Neural Network Combining with Multi-level Features
Boqing Zhu, Kele Xu, Dezhi Wang +3
Motivated by the fact that characteristics of different sound classes are highly diverse in different temporal scales and hierarchical levels, a novel deep convolutional neural net…
Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network
Kele Xu, Dawei Feng, Haibo Mi +5
Audio scene classification, the problem of predicting class labels of audio scenes, has drawn lots of attention during the last several years. However, it remains challenging and f…