86 citations · 164 across the 18 of their papers we have counts for
6 papers · 1 filter
MRSAudio: A Large-Scale Multimodal Recorded Spatial Audio Dataset with Refined Annotations
Wenxiang Guo, Changhao Pan, Zhiyuan Zhu +16
Humans rely on multisensory integration to perceive spatial environments, where auditory cues enable sound source localization in three-dimensional space. Despite the critical role…
T-vectors: Weakly Supervised Speaker Identification Using Hierarchical Transformer Model
Yanpei Shi, Mingjie Chen, Qiang Huang +1
Identifying multiple speakers without knowing where a speaker's voice is in a recording is a challenging task. This paper proposes a hierarchical network with transformer encoders…
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…
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…
Hierarchical learning for DNN-based acoustic scene classification
Yong Xu, Qiang Huang, Wenwu Wang +1
In this paper, we present a deep neural network (DNN)-based acoustic scene classification framework. Two hierarchical learning methods are proposed to improve the DNN baseline perf…
Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging
Yong Xu, Qiang Huang, Wenwu Wang +4
Environmental audio tagging aims to predict only the presence or absence of certain acoustic events in the interested acoustic scene. In this paper we make contributions to audio t…