Symphony for Speech-to-Text is a clinical-specific speech recognition API released on May 20, 2026, by Corti, a medical AI company. It offers both a WebSocket-based method for real-time transcription of medical professionals' dictation and in-office conversations, and an asynchronous batch transcription method for processing pre-recorded audio files. While general-purpose speech recognition systems act as digital stenographers, transcribing everyday language, Symphony is more akin to a medical stenographer that considers elements that can easily change in meaning within clinical documents, such as drug names, dosages, units of measurement, and dates. It aims to provide structured output that is easy for subsequent clinical agents or documentation systems to use, rather than simply converting speech to text, and can therefore be defined as an agent-ready Speech-to-Text API. General-purpose Speech-to-Text (STT) is suitable for handling typical meetings or interviews, but even small misrecognitions can significantly alter the meaning of records when dealing with similar-sounding drug names, numerical values combined with units in prescriptions, or medical history descriptions including dates. Symphony's key differentiator is that it places medical language and clinical formats at the center of its product design. Unlike approaches that pass general transcription results through a separate medical terminology dictionary or rule-based post-processor, its core value lies in providing results that reflect drugs, dosages, units, and dates within the API layer tailored to clinical dictation and medical conversations. However, based solely on the available input information, it is not possible to confirm the details of the internal acoustic model (Automatic Speech Recognition model), speaker diarization, timestamps, supported languages, accuracy metrics, and data retention policies, so a review of the official documentation is necessary before implementation. In biotechnology and clinical research, it can be used as an input layer to asynchronously transcribe audio from research participant interviews or case record reviews and then pass it to a natural language processing pipeline. For example, recorded files can be transcribed in batch to generate text including drug names, dosages, test values, and dates, and this can be connected to a Clinical Named Entity Recognition model or a data review screen to reduce the burden of manual transcription. Real-time WebSocket transcription is suitable for use in telemedicine research or clinical simulations to immediately convert speech to text and configure a subsequent summarization agent to generate a draft SOAP note. Specific sampling rates, file size limits, latency, error rates, and supported formats were not confirmed in the provided information, so official API specifications and performance validation are required before applying it to actual research protocols. Furthermore, pharmaceutical safety and clinical operations teams can configure a semi-automated workflow in which speech containing drug names, dosages, and dates is transcribed from consultation recordings and then reviewed by humans. In this case, it is more appropriate to view Symphony as a pre-processing layer that converts audio data into structured analytical input, rather than a tool for performing the final clinical judgment. Since medical data may contain sensitive information, transmission encryption, storage location, retention period, reuse of training data, and scope of regulatory compliance must be confirmed separately in the contract and official security documentation. Quantitative accuracy or clinical safety data is not currently included in the available information, so institutional validation using representative voice samples and expert review are necessary.

Symphony for Speech-to-Text is a clinical-specific speech recognition API released on May 20, 2026, by Corti, a medical AI company. It offers both a WebSocket method for real-time transcription of medical professionals' dictation and in-office conversations, and an asynchronous batch transcription method for processing pre-recorded audio files. While general-purpose speech recognizers act as digital stenographers, transcribing everyday language, Symphony is more like a medical stenographer that also considers elements that can have different meanings in clinical documents, such as drug names, dosages, units of measurement, and dates. It goes beyond simply converting speech into text.

🔬 Batch Transcription of Clinical Study Interviews: Asynchronously transcribe pre-recorded research participant interview files and pass the results, including drug name, dosage, and date, to the Clinical NER and researcher review stages. Supported file formats and sizes, processing time, and accuracy metrics require verification in the official documentation.