Gladia - What is Speaker Diarization?
One of the major obstacles for speech-to-text AI has been identifying individual speakers in a multi-speaker audio stream before transcribing the speech. This is where speaker separation, also known as diarization, comes into play. Thanks to the latest advances in ASR, diarization mechanisms have evolved significantly over the decade from a simplified acoustic-based recognition of speakers to a sophisticated dual-model approach based on embeddings containing key individual information on each speaker. Diarization is a core feature of Gladia’s Speech-to-Text API powered by optimized Whisper ASR for companies. By separating out different speakers in an audio or video recording, the features make it easier to make transcripts easier to read, summarize, and analyze. In this blog, we dive into the mechanics of speaker diarization, present its use cases, and explain how our state-of-the-art diarization API – which has just undergone a major update for improved speed and accuracy – is designe
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