Corti, a healthcare AI company based in Copenhagen, has introduced Symphony for Speech-to-Text, a clinical-grade speech recognition model designed specifically for real-time and batch medical transcription. The model achieves a notably low word error rate (WER) of just 1.4% on English medical terms, outperforming major competitors like OpenAI (17.7%), ElevenLabs, Whisper, and Parakeet. This specialization underscores the importance of tailored AI in healthcare, especially as AI agents increasingly rely on precise clinical data for decision-making. Symphony’s accuracy extends to multilingual environments, excelling in languages like German and French, and surpasses legacy systems such as Dragon Medical One. Corti’s API enables developers to build custom clinical transcription tools that enhance real-time and ambient clinical workflows. This breakthrough reflects a growing trend where specialized vertical AI models significantly outperform generalized large language models in regulated industries with complex requirements.
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