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Xinyuan Qian - IEEE Xplore Author Profile

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Author details

Xinyuan Qian

Publications

31

Citations

318

Publications by Year

20172025

Co-Authors:

Beena AhmedKaspar AlthoeferEliathamby AmbikairajahAlessio BruttiAndrea Cavallaro

Show All Co-Authors (72)

Xinyuan Qian

Affiliation

School of Computer and Communication Engineering

University of Science and Technology Beijing

Beijing, China

Publication Topics

Clear Speech,
Short-time Fourier Transform,
Convolutional Neural Network,
Long Short-term Memory,
Speech Recognition,
Speech Signal,
Attention Mechanism,
Neural Network,
Noise Recordings,
Lip Movements,
Self-supervised Learning,
Speech Enhancement

Biography

Xinyuan Qian (Member, IEEE) received the B.Eng. (with First-Class Hons.) and M.Sc. (with Distinction) degrees from the University of Edinburgh, Edinburgh, U.K., and the Ph.D. degree from Queen Mary, University of London, London, U.K. She has been a Research Fellow with the National University of Singapore since February 2020 and then become a Visiting Researcher with The Chinese University of Hong Kong (Shenzhen), Shenzhen, China. She is currently an Associate Professor with the University of Science and Technology Beijing, China. Her research interests include speech processing, audio-visual sound localization, speech enhancement, and deep learning.(Based on document published on 14 March 2023).

Publications

31

Citations

318

Publications by Year

20172025

Co-Authors:

Beena Ahmed
Kaspar Althoefer
Eliathamby Ambikairajah
Alessio Brutti
Andrea Cavallaro

Show All Co-Authors (72)

Author's Published Works

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Showing 1-25 of 31 results

Journals (20)

Conferences (10)

Early Access Articles (1)

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Xinyuan Qian(31)
Haizhou Li(17)
Jiadong Wang(9)
Qiquan Zhang(8)
Maurizio Omologo(5)
Department of Electrical and Computer Engineering, National University of Singapore, Singapore(13)
Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China(7)
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China(6)
University of Bremen, Bremen, Germany(5)
School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia(4)
IEEE Signal Processing Letters(5)
IEEE Transactions on Multimedia(4)
IEEE Transactions on Audio, Speech and Language Processing(3)
IEEE/ACM Transactions on Audio, Speech, and Language Processing(3)
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(1)
IEEE(31)
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Brighton, UK(1)
Calgary, AB, Canada(1)
Hyderabad, India(1)
London, United Kingdom(1)
New Orleans, LA, USA(1)
Microphone Array(10)
Sound Localization(10)
Clear Speech(9)
Direction Of Arrival(8)
Short-time Fourier Transform(8)

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Mamba in Speech: Towards an Alternative to Self-Attention

Xiangyu Zhang;Qiquan Zhang;Hexin Liu;Tianyi Xiao;Xinyuan Qian;Beena Ahmed;Eliathamby Ambikairajah;Haizhou Li;Julien Epps

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

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Transformer and its derivatives have achieved success in diverse tasks across computer vision, natural language processing, and speech processing. To reduce the complexity of computations within the multi-head self-attention mechanism in Transformer, Selective State Space Models (i.e., Mamba) were proposed as an alternative. Mamba exhibited its effectiveness in natural language processing and comp...Show More

Mamba in Speech: Towards an Alternative to Self-Attention

Xiangyu Zhang;Qiquan Zhang;Hexin Liu;Tianyi Xiao;Xinyuan Qian;Beena Ahmed;Eliathamby Ambikairajah;Haizhou Li;Julien Epps

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

SAV-SE: Scene-aware Audio-Visual Speech Enhancement with Selective State Space Model

Xinyuan Qian;Jiaran Gao;Yaodan Zhang;Qiquan Zhang;Hexin Liu;Leibny Paola Garcia;Haizhou Li

IEEE Journal of Selected Topics in Signal Processing

Year: 2025 | Early Access Article |

Speech enhancement plays an essential role in various applications, and the integration of visual information has been demonstrated to bring substantial advantages. However, the majority of current research concentrates on the examination of facial and lip movements, which can be compromised or entirely inaccessible in scenarios where occlusions occur or when the camera view is distant. Whereas co...Show More

SAV-SE: Scene-aware Audio-Visual Speech Enhancement with Selective State Space Model

Xinyuan Qian;Jiaran Gao;Yaodan Zhang;Qiquan Zhang;Hexin Liu;Leibny Paola Garcia;Haizhou Li

IEEE Journal of Selected Topics in Signal Processing

Year: 2025 | Early Access Article |

Improving Bird Vocalization Recognition in Open-Set Cross-Corpus Scenarios With Semantic Feature Reconstruction and Dual Strategy Scoring

Jiangjian Xie;Yingqi Wang;Xinyuan Qian;Junguo Zhang;Björn W. Schuller

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

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Automated recognition of bird vocalizations (BVs) is essential for biodiversity monitoring through passive acoustic monitoring (PAM), yet deep learning (DL) models encounter substantial challenges in open environments. These include difficulties in detecting unknown classes, extracting species-specific features, and achieving robust cross-corpus recognition. To address these challenges, this lette...Show More

Improving Bird Vocalization Recognition in Open-Set Cross-Corpus Scenarios With Semantic Feature Reconstruction and Dual Strategy Scoring

Jiangjian Xie;Yingqi Wang;Xinyuan Qian;Junguo Zhang;Björn W. Schuller

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

M2PAIR: A High-Quality Acoustic Impulse Response Computation Model

Zhiyu Li;Xinpei Zhao;Jing Wang;Xinyuan Qian;Xiang Xie

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2025 | Conference Paper |

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Acoustic Impulse Response (AIR) provides crucial spatial information about the environment, significantly enhancing audio immersion. However, achieving high perceptual quality while computing AIR in real-time for interactive audio-video media (IAVM) presents a challenging problem. This study proposes the Mesh to Parametric AIR (M2PAIR), a method for computing AIR designed for IAVM. M2PAIR integrat...Show More

M2PAIR: A High-Quality Acoustic Impulse Response Computation Model

Zhiyu Li;Xinpei Zhao;Jing Wang;Xinyuan Qian;Xiang Xie

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2025 | Conference Paper |

Audio-Visual Target Speaker Extraction With Selective Auditory Attention

Ruijie Tao;Xinyuan Qian;Yidi Jiang;Junjie Li;Jiadong Wang;Haizhou Li

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

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Audio-visual target speaker extraction (AV-TSE) aims to extract the specific person's speech from the audio mixture given auxiliary visual cues. Previous methods usually search for the target voice through speech-lip synchronization. However, this strategy mainly focuseson the existence of target speech, while ignoring the variations of the noise characteristics, i.e., interference speaker and the...Show More

Audio-Visual Target Speaker Extraction With Selective Auditory Attention

Ruijie Tao;Xinyuan Qian;Yidi Jiang;Junjie Li;Jiadong Wang;Haizhou Li

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

Enhancing Real-World Active Speaker Detection With Multi-Modal Extraction Pre-Training

Ruijie Tao;Xinyuan Qian;Rohan Kumar Das;Xiaoxue Gao;Jiadong Wang;Haizhou Li

IEEE Transactions on Multimedia

Year: 2025 | Volume: 27 | Journal Article |

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Audio-visual active speaker detection (AV-ASD) aims to identify which visible face is speaking in a scene with one or more persons. Most existing AV-ASD methods prioritize capturing speech-lip correspondence. However, there is a noticeable gap in addressing the challenges from real-world AV-ASD scenarios. Due to the presence of low-quality noisy videos in such cases, AV-ASD systems without a selec...Show More

Enhancing Real-World Active Speaker Detection With Multi-Modal Extraction Pre-Training

Ruijie Tao;Xinyuan Qian;Rohan Kumar Das;Xiaoxue Gao;Jiadong Wang;Haizhou Li

IEEE Transactions on Multimedia

Year: 2025 | Volume: 27 | Journal Article |

Analytic Class Incremental Learning for Sound Source Localization With Privacy Protection

Xinyuan Qian;Xianghu Yue;Jiadong Wang;Huiping Zhuang;Haizhou Li

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

Cited by: Papers (1)

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Sound Source Localization (SSL) enabling technology for applications such as surveillance and robotics. While traditional Signal Processing (SP)-based Sound Source Localization (SSL) methods provide analytic solutions under specific signal and noise assumptions, recent Deep Learning (DL)-based methods have significantly outperformed them. However, their success depends on extensive training data a...Show More

Analytic Class Incremental Learning for Sound Source Localization With Privacy Protection

Xinyuan Qian;Xianghu Yue;Jiadong Wang;Huiping Zhuang;Haizhou Li

IEEE Signal Processing Letters

Year: 2025 | Volume: 32 | Journal Article |

Predict-and-Update Network: Audio-Visual Speech Recognition Inspired by Human Speech Perception

Jiadong Wang;Xinyuan Qian;Haizhou Li

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

Cited by: Papers (1)

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Audio and visual signals complement each other in human speech perception, and the same applies to automatic speech recognition. The visual signal is less evident than the acoustic signal, but more robust in a complex acoustic environment, as far as speech perception is concerned. It remains a challenge how we effectively exploit the interaction between audio and visual signals for automatic speec...Show More

Predict-and-Update Network: Audio-Visual Speech Recognition Inspired by Human Speech Perception

Jiadong Wang;Xinyuan Qian;Haizhou Li

IEEE Transactions on Audio, Speech and Language Processing

Year: 2025 | Volume: 33 | Journal Article |

Attention-Based End-to-End Differentiable Particle Filter for Audio Speaker Tracking

Jinzheng Zhao;Yong Xu;Xinyuan Qian;Haohe Liu;Mark D. Plumbley;Wenwu Wang

IEEE Open Journal of Signal Processing

Year: 2024 | Volume: 5 | Journal Article |

Cited by: Papers (1)

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Particle filters (PFs) have been widely used in speaker tracking due to their capability in modeling a non-linear process or a non-Gaussian environment. However, particle filters are limited by several issues. For example, pre-defined handcrafted measurements are often used which can limit the model performance. In addition, the transition and update models are often preset which make PF less flex...Show More

Attention-Based End-to-End Differentiable Particle Filter for Audio Speaker Tracking

Jinzheng Zhao;Yong Xu;Xinyuan Qian;Haohe Liu;Mark D. Plumbley;Wenwu Wang

IEEE Open Journal of Signal Processing

Year: 2024 | Volume: 5 | Journal Article |

Audio-Visual Temporal Forgery Detection Using Embedding-Level Fusion and Multi-Dimensional Contrastive Loss

Miao Liu;Jing Wang;Xinyuan Qian;Haizhou Li

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2024 | Volume: 34, Issue: 8 | Journal Article |

Cited by: Papers (3)

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Audio-visual deepfake detection is the process of identifying and detecting deepfakes that have been generated using both audio and visual content with AI algorithms. Most existing methods primarily focus on the overall authenticity while neglecting the position of forgeries in time. This can be particularly problematic, as even a small alteration in a clip can significantly impact its meaning. Su...Show More

Audio-Visual Temporal Forgery Detection Using Embedding-Level Fusion and Multi-Dimensional Contrastive Loss

Miao Liu;Jing Wang;Xinyuan Qian;Haizhou Li

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2024 | Volume: 34, Issue: 8 | Journal Article |

Deep Cross-Modal Retrieval Between Spatial Image and Acoustic Speech

Xinyuan Qian;Wei Xue;Qiquan Zhang;Ruijie Tao;Haizhou Li

IEEE Transactions on Multimedia

Year: 2024 | Volume: 26 | Journal Article |

Cited by: Papers (2)

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Cross-modal Retrieval (CMR) is formulated for the scenarios where the queries and retrieval results are of different modalities. Existing Cross-modal Retrieval (CMR) studies mainly focus on the common contextualized information between text transcripts and images, and the synchronized event information in audio-visual recordings. Unlike all previous works, in this article, we investigate the geome...Show More

Deep Cross-Modal Retrieval Between Spatial Image and Acoustic Speech

Xinyuan Qian;Wei Xue;Qiquan Zhang;Ruijie Tao;Haizhou Li

IEEE Transactions on Multimedia

Year: 2024 | Volume: 26 | Journal Article |

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert

Jiadong Wang;Xinyuan Qian;Malu Zhang;Robby T. Tan;Haizhou Li

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

Cited by: Papers (36)

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Talking face generation, also known as speech-to-lip generation, reconstructs facial motions concerning lips given coherent speech input. The previous studies revealed the importance of lip-speech synchronization and visual quality. Despite much progress, they hardly focus on the content of lip movements i.e., the visual intelligibility of the spoken words, which is an important aspect of generati...Show More

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert

Jiadong Wang;Xinyuan Qian;Malu Zhang;Robby T. Tan;Haizhou Li

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

L$^{3}$ F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing

Wanlin Li;Meng Wang;Jiarui Li;Yao Su;Devesh K. Jha;Xinyuan Qian;Kaspar Althoefer;Hangxin Liu

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 8 | Journal Article |

Cited by: Papers (11)

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GelSight sensors that estimate contact geometry and force by reconstructing the deformation of their soft elastomer from images would yield poor force measurements when the elastomer deforms uniformly or reaches deformation saturation. Here we present an L$^{3}$ F-TOUCH sensor that considerably enhances the three-axis force sensing capability of typical GelSight sensors. Specifically, the L$^{3}$ ...Show More

L$^{3}$ F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing

Wanlin Li;Meng Wang;Jiarui Li;Yao Su;Devesh K. Jha;Xinyuan Qian;Kaspar Althoefer;Hangxin Liu

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 8 | Journal Article |

A Miniaturised Camera-based Multi-Modal Tactile Sensor

Kaspar Althoefer;Yonggen Ling;Wanlin Li;Xinyuan Qian;Wang Wei Lee;Peng Qi

2023 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2023 | Conference Paper |

Cited by: Papers (7)

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In conjunction with huge recent progress in cam-era and computer vision technology, camera-based sensors have increasingly shown considerable promise in relation to tactile sensing. In comparison to competing technologies (be they resistive, capacitive or magnetic based), they offer super-high-resolution, while suffering from fewer wiring problems. The human tactile system is composed of various t...Show More

A Miniaturised Camera-based Multi-Modal Tactile Sensor

Kaspar Althoefer;Yonggen Ling;Wanlin Li;Xinyuan Qian;Wang Wei Lee;Peng Qi

2023 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2023 | Conference Paper |

Ripple Sparse Self-Attention for Monaural Speech Enhancement

Qiquan Zhang;Hongxu Zhu;Qi Song;Xinyuan Qian;Zhaoheng Ni;Haizhou Li

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

Cited by: Papers (2)

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The use of Transformer represents a recent success in speech enhancement. However, as its core component, self-attention suffers from quadratic complexity, which is computationally prohibited for long speech recordings. Moreover, it allows each time frame to attend to all time frames, neglecting the strong local correlations of speech signals. This study presents a simple yet effective sparse self...Show More

Ripple Sparse Self-Attention for Monaural Speech Enhancement

Qiquan Zhang;Hongxu Zhu;Qi Song;Xinyuan Qian;Zhaoheng Ni;Haizhou Li

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

Device Features Based on Linear Transformation With Parallel Training Data for Replay Speech Detection

Longting Xu;Jichen Yang;Chang Huai You;Xinyuan Qian;Daiyu Huang

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

Cited by: Papers (5)

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Replay speech poses a growing threat to speaker verification systems, thus the detection of replay speech becomes increasingly important. A critical factor differentiating replay speech and genuine speech is the representation of device information. Replay speech carries physical device information that originates from recording device, playback device, and environmental noise. In this work, a dev...Show More

Device Features Based on Linear Transformation With Parallel Training Data for Replay Speech Detection

Longting Xu;Jichen Yang;Chang Huai You;Xinyuan Qian;Daiyu Huang

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

Neural-Free Attention for Monaural Speech Enhancement Toward Voice User Interface for Consumer Electronics

Moran Chen;Qiquan Zhang;Qi Song;Xinyuan Qian;Ruijin Guo;Mingjiang Wang;Deying Chen

IEEE Transactions on Consumer Electronics

Year: 2023 | Volume: 69, Issue: 4 | Journal Article |

Cited by: Papers (6)

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The traditional graphic user interface in healthcare-oriented consumer electronics faced challenges such as high operational complexity, time-consuming operations, and a high risk of infection. The adoption of voice user interface (VUI) could promote network automation with enhanced efficiency, reduced simplicity and operating expense in various applications. Given noisy operational environments, ...Show More

Neural-Free Attention for Monaural Speech Enhancement Toward Voice User Interface for Consumer Electronics

Moran Chen;Qiquan Zhang;Qi Song;Xinyuan Qian;Ruijin Guo;Mingjiang Wang;Deying Chen

IEEE Transactions on Consumer Electronics

Year: 2023 | Volume: 69, Issue: 4 | Journal Article |

Audio-Visual Cross-Attention Network for Robotic Speaker Tracking

Xinyuan Qian;Zhengdong Wang;Jiadong Wang;Guohui Guan;Haizhou Li

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

Cited by: Papers (21)

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Audio-visual signals can be used jointly for robotic perception as they complement each other. Such multi-modal sensory fusion has a clear advantage, especially under noisy acoustic conditions. Speaker localization, as an essential robotic function, was traditionally solved as a signal processing problem that now increasingly finds deep learning solutions. The question is how to fuse audio-visual ...Show More

Audio-Visual Cross-Attention Network for Robotic Speaker Tracking

Xinyuan Qian;Zhengdong Wang;Jiadong Wang;Guohui Guan;Haizhou Li

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

A Time-Frequency Attention Module for Neural Speech Enhancement

Qiquan Zhang;Xinyuan Qian;Zhaoheng Ni;Aaron Nicolson;Eliathamby Ambikairajah;Haizhou Li

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

Cited by: Papers (31)

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Speech enhancement plays an essential role in a wide range of speech processing applications. Recent studies on speech enhancement tend to investigate how to effectively capture the long-term contextual dependencies of speech signals to boost performance. However, these studies generally neglect the time-frequency (T-F) distribution information of speech spectral components, which is equally impor...Show More

A Time-Frequency Attention Module for Neural Speech Enhancement

Qiquan Zhang;Xinyuan Qian;Zhaoheng Ni;Aaron Nicolson;Eliathamby Ambikairajah;Haizhou Li

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Year: 2023 | Volume: 31 | Journal Article |

Speech-Oriented Sparse Attention Denoising for Voice User Interface Toward Industry 5.0

Hongxu Zhu;Qiquan Zhang;Peng Gao;Xinyuan Qian

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 2 | Journal Article |

Cited by: Papers (6)

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The adoption of voice user interface (VUI) will promote network automation with enhanced efficiency with reduced simplicity and operating expense in Industry 5.0. Given the noisy environments, speech denoising is indispensable for the VUI in Internet of Things (IoT) or Industrial IoT (IIoT). Despite Transformer's recent success in speech denoising, the adopted full self-attention suffers from quad...Show More

Speech-Oriented Sparse Attention Denoising for Voice User Interface Toward Industry 5.0

Hongxu Zhu;Qiquan Zhang;Peng Gao;Xinyuan Qian

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 2 | Journal Article |

Speaker Extraction With Co-Speech Gestures Cue

Zexu Pan;Xinyuan Qian;Haizhou Li

IEEE Signal Processing Letters

Year: 2022 | Volume: 29 | Journal Article |

Cited by: Papers (13)

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Speaker extraction seeks to extract the clean speech of a target speaker from a multi-talker mixture speech. There have been studies to use a pre-recorded speech sample or face image of the target speaker as the speaker cue. In human communication, co-speech gestures that are naturally timed with speech also contribute to speech perception. In this work, we explore the use of co-speech gestures se...Show More

Speaker Extraction With Co-Speech Gestures Cue

Zexu Pan;Xinyuan Qian;Haizhou Li

IEEE Signal Processing Letters

Year: 2022 | Volume: 29 | Journal Article |

Deep Audio-Visual Beamforming for Speaker Localization

Xinyuan Qian;Qiquan Zhang;Guohui Guan;Wei Xue

IEEE Signal Processing Letters

Year: 2022 | Volume: 29 | Journal Article |

Cited by: Papers (10)

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Generalized Cross Correlation (GCC) is the most popular localization technique over the past decades and can be extended with the beamforming method e.g. Steered Response Power (SRP) when multiple microphone pairs exist. Considering the promising results of Deep Learning (DL) strategies over classical approaches, in this work, instead of directly using Generalized Cross Correlation (GCC), SRP is d...Show More

Deep Audio-Visual Beamforming for Speaker Localization

Xinyuan Qian;Qiquan Zhang;Guohui Guan;Wei Xue

IEEE Signal Processing Letters

Year: 2022 | Volume: 29 | Journal Article |

Audio-Visual Tracking of Concurrent Speakers

Xinyuan Qian;Alessio Brutti;Oswald Lanz;Maurizio Omologo;Andrea Cavallaro

IEEE Transactions on Multimedia

Year: 2022 | Volume: 24 | Journal Article |

Cited by: Papers (21)

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Audio-visual tracking of an unknown number of concurrent speakers in 3D is a challenging task, especially when sound and video are collected with a compact sensing platform. In this paper, we propose a tracker that builds on generative and discriminative audio-visual likelihood models formulated in a particle filtering framework. We localize multiple concurrent speakers with a de-emphasized acoust...Show More

Audio-Visual Tracking of Concurrent Speakers

Xinyuan Qian;Alessio Brutti;Oswald Lanz;Maurizio Omologo;Andrea Cavallaro

IEEE Transactions on Multimedia

Year: 2022 | Volume: 24 | Journal Article |

SLoClas: A Database for Joint Sound Localization and Classification

Xinyuan Qian;Bidisha Sharma;Amine El Abridi;Haizhou Li

2021 24th Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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In this work, we present the development of a new database, namely Sound Localization and Classification (SLoClas) corpus, for studying and analyzing sound localization and classification. The corpus contains a total of 23.27 hours of data recorded using a 4-channel microphone array. 10 classes of sounds are played over a loudspeaker at 1.5 meters distance from the array by varying the Direction-o...Show More

SLoClas: A Database for Joint Sound Localization and Classification

Xinyuan Qian;Bidisha Sharma;Amine El Abridi;Haizhou Li

2021 24th Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)

Year: 2021 | Conference Paper |

GCC-PHAT with Speech-oriented Attention for Robotic Sound Source Localization

Jiadong Wang;Xinyuan Qian;Zihan Pan;Malu Zhang;Haizhou Li

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

Cited by: Papers (12)

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Robotic audition is a basic sense that helps robots perceive the surroundings and interact with humans. Sound Source Localization (SSL) is an essential module for a robotic system. However, the performance of most sound source localization techniques degrades in noisy and reverberant environments due to inaccurate Time Difference of Arrival (TDoA) estimation. In robotic sound source localization, ...Show More

GCC-PHAT with Speech-oriented Attention for Robotic Sound Source Localization

Jiadong Wang;Xinyuan Qian;Zihan Pan;Malu Zhang;Haizhou Li

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

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