Streaming diarization just got a major upgrade

A major upgrade to streaming diarization technology has been released, significantly improving speaker attribution in real-time applications, which is crucial for maintaining the accuracy of AI systems and preventing errors like misattributed quotes or incorrect coaching prompts. The updated model, Universal-3 Pro, outperforms competitors such as Deepgram Nova-3 by reducing false-alarm speakers by 42% and phantom turns by 91%, enhancing the accuracy of applications like AI notetakers and live captioning services. With word-level speaker labels, this upgrade allows for precise detection of speaker changes during conversations, thereby improving the overall quality of outputs for downstream AI systems. These advancements address common user frustrations, such as the need to repeat themselves or being interrupted mid-sentence, by providing clearer inputs for language models and more accurate meeting transcripts. This release demonstrates the critical role of accurate diarization in the foundational layers of voice AI systems, ensuring that applications operate more effectively and user interactions feel more like engaging with a competent, attentive human.