AssemblyAI's Universal-3.5 Pro Realtime speech-to-text model can significantly improve accuracy by incorporating conversation context. This feature allows the model to better predict and transcribe ambiguous words, names, and numbers by considering both the user's previous utterances and the agent's last spoken response. By providing this conversational history, the model can more accurately interpret short replies and spelled-out entities, which are common points of error in voice agents. AI
IMPACT Enhances voice agent performance by improving transcription accuracy for ambiguous and critical information like names and numbers.
RANK_REASON Product update for a specific speech-to-text model.
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