Speech Extraction
4 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Speech Extraction
MC_GRID
Most implemented papers
Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
jyhan03/channel-decorrelation
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First, we propose a time-domain implementation of SpeakerBeam similar to that proposed for a time-domain audio separation network (TasNet), which has achieved state-of-the-art performance for speech separation.
Target Speech Extraction Based on Blind Source Separation and X-vector-based Speaker Selection Trained with Data Augmentation
Extracting the desired speech from a mixture is a meaningful and challenging task.
Multi-channel target speech extraction with channel decorrelation and target speaker adaptation
jyhan03/channel-decorrelation
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In this work, we propose two methods for exploiting the multi-channel spatial information to extract the target speech.
DPCCN: Densely-Connected Pyramid Complex Convolutional Network for Robust Speech Separation And Extraction
Particularly, we find that the Mixture-Remix fine-tuning with DPCCN significantly outperforms the TD-SpeakerBeam for unsupervised cross-domain TSE, with around 3. 5 dB SISNR improvement on target domain test set, without any source domain performance degradation.
