ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Speech Dereverberation
Real-time joint blind speech separation and dereverberation in presence of overlapping speakers
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
The AMI meeting corpus: a pre-announcement
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
A class of frequency-domain adaptive approaches to blind multichannel identification
IEEE Transactions on Signal Processing
Estimating Dominance in Multi-Party Meetings Using Speaker Diarization
IEEE Transactions on Audio, Speech, and Language Processing
Dominance detection in a reverberated acoustic scenario
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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This paper proposes a real-time speech enhancement framework working in presence of multiple sources in reverberated environments. The aim is to automatically reduce the distortions introduced by room reverberation in the available distant speech signals and thus to achieve a significant improvement of speech quality for each speaker. The overall framework is composed by three cooperating blocks, each one fulfilling a specific task: speaker diarization, room-impulse response identification and speech dereverberation. In particular the speaker diarization algorithm is essential to pilot the operations performed in the other two stages in accordance with speakers' activity in the room. Extensive computer simulations have been performed by using a subset of the AMI database: Obtained results show the effectiveness of the approach.