speech-to-text

Transcribe audio to text with Scribe v2 - supports 90+ languages, speaker diarization, and word-level timestamps. Setup: See Installation Guide . For JavaScript, use @elevenlabs/* packages only. Word-level timestamps include type classification and speaker identification: Identify WHO said WHAT - the model labels each word with a speaker ID, useful for meetings, interviews, or any multi-speaker audio: Help the model recognize specific words it might otherwise mishear - product names, technical jargon, or unusual spellings (up to 100 terms): Automatic detection with optional language hint: Audio: MP3, WAV, M4A, FLAC, OGG, WebM, AAC, AIFF, Opus Video: MP4, AVI, MKV, MOV, WMV, FLV, WebM, MPEG, 3GPP Limits: Up to 3GB file size, 10 hours duration Word types: Common errors: Monitor usage via request-id response header: For live transcription with ultra-low latency (~150ms), use the real-time API. The real-time API produces two types of transcripts: A "commit" tells the model to finalize the current segment. You can commit manually (e.g., when the user pauses) or use Voice Activity Detection (VAD) to auto-commit on silence. See real-time references for complete documentation. - word - An actual spoken word - spacing - Whitespace between words (useful for precise timing) - audio_event - Non-speech sounds the model detected (laughter, applause, music, etc.) - 401 : Invalid API key -...