A new approach for speaker tracking in reverberant environment
Signal Processing
Passive acoustic source localization for video camera steering
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Nonlinear filtering for speaker tracking in noisy and reverberant environments
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
EURASIP Journal on Applied Signal Processing
Microphone array speaker localizers using spatial-temporal information
EURASIP Journal on Applied Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
IEEE Transactions on Audio, Speech, and Language Processing
The AIT 3D Audio / Visual Person Tracker for CLEAR 2007
Multimodal Technologies for Perception of Humans
Measurement combination for acoustic source localization in a room environment
EURASIP Journal on Audio, Speech, and Music Processing - Intelligent Audio, Speech, and Music Processing Applications
Audio-visual active speaker tracking in cluttered indoors environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Acoustic source localization and tracking using track before detect
IEEE Transactions on Audio, Speech, and Language Processing
Diffuse reverberation model for efficient image-source simulation of room impulse responses
IEEE Transactions on Audio, Speech, and Language Processing
Robotics and Autonomous Systems
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Tracking of multidimensional TDOA for multiple sources with distributed microphone pairs
Computer Speech and Language
Auditory inspired methods for localization of multiple concurrent speakers
Computer Speech and Language
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In noisy and reverberant environments, the problem of acoustic source localisation and tracking (ASLT) using an array of microphones presents a number of challenging difficulties. One of the main issues when considering real-world situations involving human speakers is the temporally discontinuous nature of speech signals: the presence of silence gaps in the speech can easily misguide the tracking algorithm, even in practical environments with low to moderate noise and reverberation levels. A natural extension of currently available sound source tracking algorithms is the integration of a voice activity detection (VAD) scheme. We describe a new ASLT algorithm based on a particle filtering (PF) approach, where VAD measurements are fused within the statistical framework of the PF implementation. Tracking accuracy results for the proposed method is presented on the basis of synthetic audio samples generated with the image method, whereas performance results obtained with a real-time implementation of the algorithm, and using real audio data recorded in a reverberant room, are published elsewhere. Compared to a previously proposed PF algorithm, the experimental results demonstrate the improved robustness of the method described in this work when tracking sources emitting real-world speech signals, which typically involve significant silence gaps between utterances.