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ElevenLabs Launches Scribe, a Cutting-Edge Speech-to-Text Model

Image Source: ChatGPT-4o
ElevenLabs Launches Scribe, a Cutting-Edge Speech-to-Text Model
ElevenLabs has launched Scribe, a cutting-edge automatic speech recognition (ASR) model that delivers the world’s most accurate transcriptions. Designed for real-world audio challenges, Scribe supports 99 languages and offers word-level timestamps, speaker diarization, and audio-event tagging for structured and seamless integration.
Industry-Leading Accuracy
In benchmark tests across FLEURS and Common Voice datasets, Scribe consistently outperforms top ASR models, including Gemini 2.0 Flash, Whisper Large V3, and Deepgram Nova-3. It delivers:
98.7% accuracy in Italian
96.7% accuracy in English
Improved performance in 97 other languages
Scribe also makes ASR more accessible by significantly reducing errors in traditionally underserved languages such as Serbian, Cantonese, and Malayalam, where competing models struggle with 40%+ word error rates.
How to Access Scribe
Scribe is available through:
API Integration – Developers can access structured JSON transcripts with speaker diarization, timestamps, and non-speech event markers (e.g., laughter).
ElevenLabs Dashboard – Users can upload audio or video files to generate formatted transcripts instantly.
Real-Time Version Coming Soon – A low-latency version for live transcription is in development.
Looking Ahead
With unmatched accuracy and multilingual capabilities, Scribe is poised to set a new standard in speech-to-text AI. Whether for meeting transcriptions, movie subtitles, or real-time speech applications, this model promises faster, more precise, and universally accessible ASR technology.
🔗 Get Started with Scribe: API Documentation | Try in the ElevenLabs Dashboard
Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.