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Accurate and scalable speech-to-text API for developers and enterprises.

Rev AI offers a speech-to-text API designed for developers needing high accuracy and scalability. The API supports both asynchronous and real-time streaming transcription, handling over 57 languages. It's built on proprietary models trained with millions of hours of human-verified speech data, ensuring low word error rates (WER) across diverse accents and audio conditions. Key features include language identification, sentiment analysis, and topic extraction. The platform provides developer-friendly SDKs for Python, Node.js, and more, with flexible output formats like JSON and SRT. It caters to industries like legal, media, enterprise, and education, providing solutions for captioning, compliance, and customer insights. Enterprise-grade security with SOC II, HIPAA, and GDPR compliance ensures data protection.
Rev AI offers a speech-to-text API designed for developers needing high accuracy and scalability.
Explore all tools that specialize in transcribe audio to text. This domain focus ensures Rev AI delivers optimized results for this specific requirement.
Explore all tools that specialize in sentiment analysis. This domain focus ensures Rev AI delivers optimized results for this specific requirement.
Provides precise word-level timestamps for enhanced content searchability and analysis.
Automatically detects the language of the audio input for accurate transcription.
Analyzes the sentiment expressed in the transcribed text to provide insights into customer emotions.
Identifies key topics discussed in the audio to facilitate content summarization and categorization.
Allows users to define domain-specific terminology and unique names for improved transcription accuracy.
Supports transcription in 57+ languages with consistently low WER.
Sign up for a free Rev AI account.
Generate an access token from the Access Token page.
Submit an audio file or stream to the API using the access token.
Check the status of the transcription job via API calls.
Retrieve the transcript in JSON or plaintext format.
Integrate the API with SDKs for Python, Node.js, or other languages.
Utilize webhooks for asynchronous notifications on job completion.
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