Diart: A Python Library for Real-Time Speaker Diarization
Résumé
The term "speaker diarization" denotes the problem of determining "who speaks when" in a recorded conversation. Among other reasons, it has attracted the attention of the speech research community because of its ability to improve transcription performance, readability and exploitability. Speaker diarization in real-time holds the potential to accelerate and cement the adoption of this technology in our everyday lives. However, although "offline" systems today achieve outstanding performance in pre-recorded conversations, additional problems of "online" real-time diarization, like limited context and low latency, require flexible and efficient solutions enabling both research and production-ready applications. We introduce a Python package called Diart to address real-time speaker diarization in an efficient and flexible way.
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