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相关论文: Data-Efficient Low-Complexity Acoustic Scene Class…

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This paper presents the Low-Complexity Acoustic Scene Classification with Device Information Task of the DCASE 2025 Challenge, along with its baseline system. Continuing the focus on low-complexity models, data efficiency, and device…

音频与语音处理 · 电气工程与系统科学 2026-05-08 Florian Schmid , Paul Primus , Toni Heittola , Annamaria Mesaros , Irene Martín-Morató , Gerhard Widmer

This paper presents the details of Task 1A Acoustic Scene Classification in the DCASE 2021 Challenge. The task targeted development of low-complexity solutions with good generalization properties. The provided baseline system is based on a…

音频与语音处理 · 电气工程与系统科学 2021-07-21 Irene Martín-Morató , Toni Heittola , Annamaria Mesaros , Tuomas Virtanen

This paper presents an analysis of the Low-Complexity Acoustic Scene Classification task in DCASE 2022 Challenge. The task was a continuation from the previous years, but the low-complexity requirements were changed to the following: the…

In this technical report, we describe the SNTL-NTU team's submission for Task 1 Data-Efficient Low-Complexity Acoustic Scene Classification of the detection and classification of acoustic scenes and events (DCASE) 2024 challenge. Three…

声音 · 计算机科学 2024-09-19 Jin Jie Sean Yeo , Ee-Leng Tan , Jisheng Bai , Santi Peksi , Woon-Seng Gan

This paper presents the details of the Audio-Visual Scene Classification task in the DCASE 2021 Challenge (Task 1 Subtask B). The task is concerned with classification using audio and video modalities, using a dataset of synchronized…

音频与语音处理 · 电气工程与系统科学 2021-07-21 Shanshan Wang , Toni Heittola , Annamaria Mesaros , Tuomas Virtanen

This paper presents the details of Task 1: Acoustic Scene Classification in the DCASE 2020 Challenge. The task consists of two subtasks: classification of data from multiple devices, requiring good generalization properties, and…

音频与语音处理 · 电气工程与系统科学 2020-11-03 Toni Heittola , Annamaria Mesaros , Tuomas Virtanen

This paper introduces the acoustic scene classification task of DCASE 2018 Challenge and the TUT Urban Acoustic Scenes 2018 dataset provided for the task, and evaluates the performance of a baseline system in the task. As in previous years…

音频与语音处理 · 电气工程与系统科学 2018-10-12 Annamaria Mesaros , Toni Heittola , Tuomas Virtanen

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-convolution network which consists of four modules, including…

音频与语音处理 · 电气工程与系统科学 2024-06-13 Yanxiong Li , Jiaxin Tan , Guoqing Chen , Jialong Li , Yongjie Si , Qianhua He

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 classifying audio samples of multiple devices with a…

音频与语音处理 · 电气工程与系统科学 2023-06-06 Yanxiong Li , Wenchang Cao , Wei Xie , Qisheng Huang , Wenfeng Pang , Qianhua He

In this paper, we present a robust and low complexity system for Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording. We first construct an ASC baseline system in which a novel…

声音 · 计算机科学 2022-03-24 Lam Pham , Khoa Dinh , Dat Ngo , Hieu Tang , Alexander Schindler

The Detection and Classification of Acoustic Scenes and Events (DCASE) consists of five audio classification and sound event detection tasks: 1) Acoustic scene classification, 2) General-purpose audio tagging of Freesound, 3) Bird audio…

声音 · 计算机科学 2019-12-10 Qiuqiang Kong , Turab Iqbal , Yong Xu , Wenwu Wang , Mark D. Plumbley

Acoustic scene classification is an automatic listening problem that aims to assign an audio recording to a pre-defined scene based on its audio data. Over the years (and in past editions of the DCASE) this problem has often been solved…

Acoustic scene classification (ASC) is one of the most popular problems in the field of machine listening. The objective of this problem is to classify an audio clip into one of the predefined scenes using only the audio data. This problem…

This paper presents a low-complexity framework for acoustic scene classification (ASC). Most of the frameworks designed for ASC use convolutional neural networks (CNNs) due to their learning ability and improved performance compared to…

音频与语音处理 · 电气工程与系统科学 2022-07-26 Arshdeep Singh , Mark D. Plumbley

The Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge focuses on audio tagging, sound event detection and spatial localisation. DCASE 2019 consists of five tasks: 1) acoustic scene classification, 2) audio…

声音 · 计算机科学 2019-04-16 Qiuqiang Kong , Yin Cao , Turab Iqbal , Yong Xu , Wenwu Wang , Mark D. Plumbley

This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis. Recent advances in sound synthesis and generative models have enabled the creation of realistic and diverse audio content. We introduce a standardized evaluation…

The Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge focuses on audio tagging, sound event detection and spatial localisation. DCASE 2019 consists of five tasks: 1) acoustic scene classification, 2) audio…

声音 · 计算机科学 2019-06-11 Qiuqiang Kong , Yin Cao , Turab Iqbal , Yong Xu , Wenwu Wang , Mark D. Plumbley

In this paper we present our work on Task 1 Acoustic Scene Classi- fication and Task 3 Sound Event Detection in Real Life Recordings. Among our experiments we have low-level and high-level features, classifier optimization and other…

This paper proposes a benchmark of submissions to Detection and Classification Acoustic Scene and Events 2021 Challenge (DCASE) Task 4 representing a sampling of the state-of-the-art in Sound Event Detection task. The submissions are…

音频与语音处理 · 电气工程与系统科学 2024-01-02 Francesca Ronchini , Romain Serizel

This technical report describes the details of our TASK1A submission of the DCASE2021 challenge. The goal of the task is to design an audio scene classification system for device-imbalanced datasets under the constraints of model…

声音 · 计算机科学 2022-10-26 Byeonggeun Kim , Seunghan Yang , Jangho Kim , Simyung Chang
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