23 citations · 50 across the 18 of their papers we have counts for
16 papers · 1 filter
TriA Pipeline: A Large-Scale Automatic Audio Annotation Pipeline For Audio Classification In Specific Scenarios
Hong Lyu, Mingru Yang, Qianhua He +3
There are some datasets of varying scales for audio classification (AC) applied to different tasks. However, annotated data is limited for most scenarios, such as domestic environm…
Fully Few-shot Class-incremental Audio Classification Using Multi-level Embedding Extractor and Ridge Regression Classifier
Yongjie Si, Yanxiong Li, Jiaxin Tan +2
In the task of Few-shot Class-incremental Audio Classification (FCAC), training samples of each base class are required to be abundant to train model. However, it is not easy to co…
Fully Few-shot Class-incremental Audio Classification Using Expandable Dual-embedding Extractor
Yongjie Si, Yanxiong Li, Jialong Li +2
It's assumed that training data is sufficient in base session of few-shot class-incremental audio classification. However, it's difficult to collect abundant samples for model trai…
Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution Network
Yanxiong Li, Jiaxin Tan, Guoqing Chen +3
This work is an improved system that we submitted to task 1 of DCASE2023 challenge. We propose a method of low-complexity acoustic scene classification by a parallel attention-conv…
Lightweight Speaker Verification Using Transformation Module with Feature Partition and Fusion
Yanxiong Li, Zhongjie Jiang, Qisheng Huang +2
Although many efforts have been made on decreasing the model complexity for speaker verification, it is still challenging to deploy speaker verification systems with satisfactory r…
Domestic Activities Classification from Audio Recordings Using Multi-scale Dilated Depthwise Separable Convolutional Network
Yufei Zeng, Yanxiong Li, Zhenfeng Zhou +2
Domestic activities classification (DAC) from audio recordings aims at classifying audio recordings into pre-defined categories of domestic activities, which is an effective way fo…
Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration
Yanxiong Li, Mingle Liu, Wucheng Wang +2
Recent efforts have been made on acoustic scene classification in the audio signal processing community. In contrast, few studies have been conducted on acoustic scene clustering,…
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet
Yanxiong Li, Wenchang Cao, Wei Xie +3
We present a work on low-complexity acoustic scene classification (ASC) with multiple devices, namely the subtask A of Task 1 of the DCASE2021 challenge. This subtask focuses on cl…
Few-shot Class-incremental Audio Classification Using Stochastic Classifier
Yanxiong Li, Wenchang Cao, Jialong Li +2
It is generally assumed that number of classes is fixed in current audio classification methods, and the model can recognize pregiven classes only. When new classes emerge, the mod…
Speaker verification using attentive multi-scale convolutional recurrent network
Yanxiong Li, Zhongjie Jiang, Wenchang Cao +1
In this paper, we propose a speaker verification method by an Attentive Multi-scale Convolutional Recurrent Network (AMCRN). The proposed AMCRN can acquire both local spatial infor…
Few-Shot Speaker Identification Using Lightweight Prototypical Network with Feature Grouping and Interaction
Yanxiong Li, Hao Chen, Wenchang Cao +2
Existing methods for few-shot speaker identification (FSSI) obtain high accuracy, but their computational complexities and model sizes need to be reduced for lightweight applicatio…
Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes
Yanxiong Li, Wenchang Cao, Wei Xie +2
Most existing methods for audio classification assume that the vocabulary of audio classes to be classified is fixed. When novel (unseen) audio classes appear, audio classification…
Domestic Activity Clustering from Audio via Depthwise Separable Convolutional Autoencoder Network
Yanxiong Li, Wenchang Cao, Konstantinos Drossos +1
Automatic estimation of domestic activities from audio can be used to solve many problems, such as reducing the labor cost for nursing the elderly people. This study focuses on sol…
Few-Shot Speaker Identification Using Depthwise Separable Convolutional Network with Channel Attention
Yanxiong Li, Wucheng Wang, Hao Chen +3
Although few-shot learning has attracted much attention from the fields of image and audio classification, few efforts have been made on few-shot speaker identification. In the tas…
Domestic activities clustering from audio recordings using convolutional capsule autoencoder network
Ziheng Lin, Yanxiong Li, Zhangjin Huang +4
Recent efforts have been made on domestic activities classification from audio recordings, especially the works submitted to the challenge of DCASE (Detection and Classification of…
Sound event detection via dilated convolutional recurrent neural networks
Yanxiong Li, Mingle Liu, Konstantinos Drossos +1
Convolutional recurrent neural networks (CRNNs) have achieved state-of-the-art performance for sound event detection (SED). In this paper, we propose to use a dilated CRNN, namely…