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A review of speaker diarization: Recent advances with deep learning
Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …
Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
Integrating end-to-end neural and clustering-based diarization: Getting the best of both worlds
Recent diarization technologies can be categorized into two approaches, ie, clustering and
end-to-end neural approaches, which have different pros and cons. The clustering-based …
end-to-end neural approaches, which have different pros and cons. The clustering-based …
Attention-based encoder-decoder end-to-end neural diarization with embedding enhancer
Deep neural network-based systems have significantly improved the performance of
speaker diarization tasks. However, end-to-end neural diarization (EEND) systems often …
speaker diarization tasks. However, end-to-end neural diarization (EEND) systems often …