Shypd.aiThe largest open index of AI toolsSpeech-Separation-Paper-Tutorial is a Research & Education tool that provides a comprehensive collection of speech separation papers, models, and resources. It covers developments from 2016-2025, offering insights into various architectures and performance metrics.
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Speech-Separation-Paper-Tutorial is an invaluable resource for anyone interested in speech separation based on neural networks. This GitHub repository compiles a comprehensive collection of papers, models, and related resources spanning from 2016 to 2025. It offers detailed overviews, model timelines, and performance comparisons across various datasets like WSJ0-2Mix, WHAM!, and LibriMix. Users can explore different model categories, including deterministic vs. generative approaches, network architectures like dual-path and Conv-TasNet, and learning methods such as predictive and unsupervised techniques. The tutorial also delves into multi-modal speech separation, evaluation metrics like SI-SNRi and SDRi, and provides information on key datasets, making it a central hub for academic research and development in the field.
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