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The audio source separation tasks, such as speech enhancement, speech separation, and music source separation, have achieved impressive performance in recent studies. The powerful modeling capabilities of deep neural networks give us hope…

音频与语音处理 · 电气工程与系统科学 2021-07-15 Lu Zhang , Chenxing Li , Feng Deng , Xiaorui Wang

This technical report presents our submission to Task 3 of the DCASE 2025 Challenge: Stereo Sound Event Localization and Detection (SELD) in Regular Video Content. We address the audio-only task in this report and introduce several key…

音频与语音处理 · 电气工程与系统科学 2025-07-02 Jun-Wei Yeow , Ee-Leng Tan , Santi Peksi , Woon-Seng Gan

We present Spatial LibriSpeech, a spatial audio dataset with over 650 hours of 19-channel audio, first-order ambisonics, and optional distractor noise. Spatial LibriSpeech is designed for machine learning model training, and it includes…

We introduce the first Natural Office Talkers in Settings of Far-field Audio Recordings (``NOTSOFAR-1'') Challenge alongside datasets and baseline system. The challenge focuses on distant speaker diarization and automatic speech recognition…

This report describes our systems submitted for the DCASE2024 Task 3 challenge: Audio and Audiovisual Sound Event Localization and Detection with Source Distance Estimation (Track B). Our main model is based on the audio-visual (AV)…

音频与语音处理 · 电气工程与系统科学 2024-10-30 Davide Berghi , Philip J. B. Jackson

This study presents an audio-visual information fusion approach to sound event localization and detection (SELD) in low-resource scenarios. We aim at utilizing audio and video modality information through cross-modal learning and…

音频与语音处理 · 电气工程与系统科学 2024-06-24 Ya Jiang , Qing Wang , Jun Du , Maocheng Hu , Pengfei Hu , Zeyan Liu , Shi Cheng , Zhaoxu Nian , Yuxuan Dong , Mingqi Cai , Xin Fang , Chin-Hui Lee

Sound event localization and detection (SELD) combines two subtasks: sound event detection (SED) and direction of arrival (DOA) estimation. SELD is usually tackled as an audio-only problem, but visual information has been recently included.…

音频与语音处理 · 电气工程与系统科学 2023-12-15 Davide Berghi , Peipei Wu , Jinzheng Zhao , Wenwu Wang , Philip J. B. Jackson

This paper summarizes the work done by the authors for the Zero Resource Speech Challenge organized in the technical program of Interspeech 2015. The goal of the challenge is to discover linguistic units directly from unlabeled speech data.…

计算与语言 · 计算机科学 2015-06-09 Cheng-Tao Chung , Cheng-Yu Tsai , Hsiang-Hung Lu , Yuan-ming Liou , Yen-Chen Wu , Yen-Ju Lu , Hung-yi Lee , Lin-shan Lee

The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a DNS challenge special session at INTERSPEECH and ICASSP…

This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the…

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

The Mice Autism Detection via Ultrasound Vocalization (MADUV) Challenge introduces the first INTERSPEECH challenge focused on detecting autism spectrum disorder (ASD) in mice through their vocalizations. Participants are tasked with…

Sound event localization and detection (SELD) is a joint task of sound event detection and direction-of-arrival estimation. In DCASE 2022 Task 3, types of data transform from computationally generated spatial recordings to recordings of…

音频与语音处理 · 电气工程与系统科学 2022-09-12 Jinbo Hu , Yin Cao , Ming Wu , Qiuqiang Kong , Feiran Yang , Mark D. Plumbley , Jun Yang

This technical report details our systems submitted for Task 3 of the DCASE 2024 Challenge: Audio and Audiovisual Sound Event Localization and Detection (SELD) with Source Distance Estimation (SDE). We address only the audio-only SELD with…

音频与语音处理 · 电气工程与系统科学 2024-07-15 Jun Wei Yeow , Ee-Leng Tan , Jisheng Bai , Santi Peksi , Woon-Seng Gan

This paper explores enabling large language models (LLMs) to understand spatial information from multichannel audio, a skill currently lacking in auditory LLMs. By leveraging LLMs' advanced cognitive and inferential abilities, the aim is to…

声音 · 计算机科学 2024-06-17 Changli Tang , Wenyi Yu , Guangzhi Sun , Xianzhao Chen , Tian Tan , Wei Li , Jun Zhang , Lu Lu , Zejun Ma , Yuxuan Wang , Chao Zhang

Our systems submitted to the DCASE2020 task~3: Sound Event Localization and Detection (SELD) are described in this report. We consider two systems: a single-stage system that solve sound event localization~(SEL) and sound event…

音频与语音处理 · 电气工程与系统科学 2020-10-09 Kazuki Shimada , Naoya Takahashi , Shusuke Takahashi , Yuki Mitsufuji

Sound event localization and detection (SELD) is a combined task of identifying the sound event and its direction. Deep neural networks (DNNs) are utilized to associate them with the sound signals observed by a microphone array. Although…

音频与语音处理 · 电气工程与系统科学 2022-02-18 Kento Nagatomo , Masahiro Yasuda , Kohei Yatabe , Shoichiro Saito , Yasuhiro Oikawa

Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were organized during 2019-2023 to stimulate research in deep speech…

This paper describes sound event localization and detection (SELD) for spatial audio recordings captured by firstorder ambisonics (FOA) microphones. In this task, one may train a deep neural network (DNN) using FOA data annotated with the…

声音 · 计算机科学 2024-10-31 Yoto Fujita , Yoshiaki Bando , Keisuke Imoto , Masaki Onishi , Kazuyoshi Yoshii

This technical report describes two methods that were developed for Task 2 of the DCASE 2020 challenge. The challenge involves an unsupervised learning to detect anomalous sounds, thus only normal machine working condition samples are…

音频与语音处理 · 电气工程与系统科学 2020-06-22 Alexandrine Ribeiro , Luis Miguel Matos , Pedro Jose Pereira , Eduardo C. Nunes , Andre L. Ferreira , Paulo Cortez , Andre Pilastri