Major UI overhaul plans; Other random docs
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Michael Chihlas
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.agent/skills/speech-to-text/references/transcription-options.md
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.agent/skills/speech-to-text/references/transcription-options.md
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# Transcription Options
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## Request Parameters
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| Parameter | Type | Required | Description |
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|-----------|------|----------|-------------|
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| `file` | file | Yes | Audio or video file to transcribe |
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| `model_id` | string | Yes | `scribe_v2` (or legacy `scribe_v1`) for batch transcription |
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| `language_code` | string | No | Language hint (ISO 639-1 or ISO 639-3, e.g., `en` or `eng`) |
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| `timestamps_granularity` | string | No | `none`, `word`, or `character` (default: `word`) |
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| `diarize` | boolean | No | Enable speaker diarization (up to 32 speakers for batch) |
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| `num_speakers` | integer | No | Maximum speakers to detect (up to 32 for batch) |
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| `diarization_threshold` | number | No | Tune diarization sensitivity when `diarize=true` |
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| `keyterms` | array | No | Terms to bias transcription (up to 100) |
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| `tag_audio_events` | boolean | No | Detect non-speech sounds (laughter, applause) |
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| `entity_detection` | string or array | No | Detect entities (e.g., `pii`, `phi`, `pci`, `offensive_language`) |
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| `use_multi_channel` | boolean | No | Split multichannel audio into separate transcripts |
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| `cloud_storage_url` | string | No | HTTPS URL to transcribe instead of uploading a file |
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| `webhook` | boolean | No | Process async and send result to webhook |
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| `webhook_metadata` | string or object | No | Custom metadata included in webhook responses |
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## Python Example
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```python
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from elevenlabs.client import ElevenLabs
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client = ElevenLabs()
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with open("audio.mp3", "rb") as audio_file:
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result = client.speech_to_text.convert(
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file=audio_file,
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model_id="scribe_v2",
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language_code="eng",
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timestamps_granularity="word",
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diarize=True,
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keyterms=["ElevenLabs", "Scribe"]
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)
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```
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## JavaScript Example
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```javascript
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import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
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import { createReadStream } from "fs";
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const client = new ElevenLabsClient();
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const result = await client.speechToText.convert({
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file: createReadStream("audio.mp3"),
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modelId: "scribe_v2",
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languageCode: "eng",
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timestampsGranularity: "word",
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diarize: true,
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keyterms: ["ElevenLabs", "Scribe"],
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});
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```
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## cURL Example
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```bash
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curl -X POST "https://api.elevenlabs.io/v1/speech-to-text" \
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-H "xi-api-key: $ELEVENLABS_API_KEY" \
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-F "file=@audio.mp3" \
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-F "model_id=scribe_v2" \
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-F "language_code=eng" \
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-F "timestamps_granularity=word" \
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-F "diarize=true"
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```
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## Response Structure
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```json
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{
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"text": "The complete transcribed text from the audio file.",
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"language_code": "eng",
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"language_probability": 0.98,
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"words": [
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{
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"text": "The",
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"start": 0.0,
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"end": 0.15,
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"type": "word",
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"speaker_id": "speaker_0"
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},
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{
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"text": " ",
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"start": 0.15,
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"end": 0.16,
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"type": "spacing",
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"speaker_id": "speaker_0"
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}
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]
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}
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```
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## Response Fields
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| Field | Type | Description |
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|-------|------|-------------|
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| `text` | string | Full transcription text |
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| `language_code` | string | Detected language (ISO 639-1 or ISO 639-3) |
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| `language_probability` | float | Confidence in detection (0-1) |
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| `words` | array | Word-level timestamps (if requested) |
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| `words[].text` | string | The transcribed word or spacing |
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| `words[].start` | float | Start time in seconds |
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| `words[].end` | float | End time in seconds |
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| `words[].type` | string | `word`, `spacing`, or `audio_event` |
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| `words[].speaker_id` | string | Speaker identifier (if diarization enabled) |
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## Supported Languages (90+)
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Common languages (ISO 639-3 codes):
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| Code | Language | Code | Language |
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|------|----------|------|----------|
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| `eng` | English | `jpn` | Japanese |
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| `spa` | Spanish | `kor` | Korean |
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| `fra` | French | `zho` | Mandarin |
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| `deu` | German | `ara` | Arabic |
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| `ita` | Italian | `hin` | Hindi |
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| `por` | Portuguese | `tur` | Turkish |
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| `nld` | Dutch | `swe` | Swedish |
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| `pol` | Polish | `dan` | Danish |
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| `rus` | Russian | `fin` | Finnish |
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Full list: Afrikaans, Amharic, Armenian, Azerbaijani, Belarusian, Bengali, Bosnian, Bulgarian, Burmese, Cantonese, Catalan, Cebuano, Croatian, Czech, Estonian, Filipino, Georgian, Greek, Gujarati, Hausa, Hebrew, Hungarian, Icelandic, Indonesian, Irish, Javanese, Kannada, Kazakh, Khmer, Kyrgyz, Lao, Latvian, Lithuanian, Luxembourgish, Macedonian, Malay, Malayalam, Maltese, Māori, Marathi, Mongolian, Nepali, Norwegian, Odia, Pashto, Persian, Punjabi, Romanian, Serbian, Shona, Sindhi, Slovak, Slovenian, Somali, Swahili, Tamil, Tajik, Telugu, Thai, Ukrainian, Urdu, Uzbek, Vietnamese, Welsh, Wolof, Xhosa, Yoruba, Zulu.
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## Format Requirements
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**Audio:** MP3, WAV, M4A, FLAC, OGG, WebM, AAC, AIFF, Opus
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**Video:** MP4, AVI, MKV, MOV, WMV, FLV, WebM, MPEG, 3GPP
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**Limits:**
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- Maximum file size: 3GB
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- Maximum duration: 10 hours
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## Use Cases
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### Subtitle Generation with Speakers
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```python
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result = client.speech_to_text.convert(
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file=audio_file,
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model_id="scribe_v2",
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timestamps_granularity="word",
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diarize=True
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)
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# Generate SRT with speaker labels
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for i, word in enumerate(result.words, 1):
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if word.type == "word":
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print(f"[{word.speaker_id}] {word.text} ({word.start:.2f}s)")
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```
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### Meeting Transcription with Custom Terms
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```python
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with open("meeting.mp3", "rb") as f:
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result = client.speech_to_text.convert(
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file=f,
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model_id="scribe_v2",
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diarize=True,
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keyterms=["Q4 forecast", "revenue target", "ACME Corp"]
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)
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# Group by speaker
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current_speaker = None
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for word in result.words:
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if word.type == "word":
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if word.speaker_id != current_speaker:
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current_speaker = word.speaker_id
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print(f"\n[{current_speaker}]:", end=" ")
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print(word.text, end="")
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```
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