activity
20162026
most citedWavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research

138 citations · 1.2k across the 72 of their papers we have counts for

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Showing 2017Show all

6 papers · 1 filter

cs.SD2017★ 1 cited

A joint separation-classification model for sound event detection of weakly labelled data

Qiuqiang Kong, Yong Xu, Wenwu Wang +1

Source separation (SS) aims to separate individual sources from an audio recording. Sound event detection (SED) aims to detect sound events from an audio recording. We propose a jo…

cs.SD2017★ 8 cited

Audio Set classification with attention model: A probabilistic perspective

Qiuqiang Kong, Yong Xu, Wenwu Wang +1

This paper investigates the classification of the Audio Set dataset. Audio Set is a large scale weakly labelled dataset of sound clips. Previous work used multiple instance learnin…

cs.SD2017★ 13 cited

Large-scale weakly supervised audio classification using gated convolutional neural network

Yong Xu, Qiuqiang Kong, Wenwu Wang +1

In this paper, we present a gated convolutional neural network and a temporal attention-based localization method for audio classification, which won the 1st place in the large-sca…

cs.SD2017★ 33 cited

Surrey-cvssp system for DCASE2017 challenge task4

Yong Xu, Qiuqiang Kong, Wenwu Wang +1

In this technique report, we present a bunch of methods for the task 4 of Detection and Classification of Acoustic Scenes and Events 2017 (DCASE2017) challenge. This task evaluates…

cs.SD2017★ 7 cited

Attention and Localization based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging

Yong Xu, Qiuqiang Kong, Qiang Huang +2

Audio tagging aims to perform multi-label classification on audio chunks and it is a newly proposed task in the Detection and Classification of Acoustic Scenes and Events 2016 (DCA…

cs.SD2017★ 10 cited

Convolutional Gated Recurrent Neural Network Incorporating Spatial Features for Audio Tagging

Yong Xu, Qiuqiang Kong, Qiang Huang +2

Environmental audio tagging is a newly proposed task to predict the presence or absence of a specific audio event in a chunk. Deep neural network (DNN) based methods have been succ…