# Transcribe Interview to Text — for Journalists & Researchers (`sian.agency/transcribe-interview-to-text`) Actor Transcribe interviews and recorded conversations to text. Speaker labels for interviewer and guest, word-level timestamps, SRT/VTT. Try free. - **URL**: https://apify.com/sian.agency/transcribe-interview-to-text.md - **Developed by:** [SIÁN OÜ](https://apify.com/sian.agency) (community) - **Categories:** Automation, Videos - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.15 / 1,000 second of video processeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Transcribe Interview to Text — for Journalists & Researchers [![SIÁN Agency Store](https://img.shields.io/badge/Store-SI%C3%81N%20Agency-97cc64)](https://apify.com/sian.agency?fpr=sian) [![Telegram Support](https://img.shields.io/badge/Telegram-Support%20Group-0088cc?logo=telegram)](https://t.me/+vyh1sRE08sAxMGRi) [![Instagram AI Transcript Extractor](https://img.shields.io/badge/Platform-Instagram-E4405F)](https://apify.com/sian.agency/instagram-ai-transcript-extractor?fpr=sian) [![Best TikTok AI Transcript Extractor](https://img.shields.io/badge/Platform-TikTok-25F4EE)](https://apify.com/sian.agency/best-tiktok-ai-transcript-extractor?fpr=sian) [![YouTube Shorts AI Transcript Extractor](https://img.shields.io/badge/Platform-YouTube%20Shorts-FF0000)](https://apify.com/sian.agency/youtube-shorts-ai-transcript-and-metadata-extractor?fpr=sian) [![Facebook AI Transcript Extractor](https://img.shields.io/badge/Platform-Facebook-1877F2)](https://apify.com/sian.agency/facebook-ai-transcript-extractor?fpr=sian) > **Transcribe interviews and recorded conversations to text.** Built for journalists, qualitative researchers, market researchers, and anyone with hours of interview tape. Speaker labels for interviewer and guest, word-level timestamps for precise quote extraction, SRT/VTT subtitles, 99+ languages. --- ### How to transcribe an interview in 4 steps 1. **Upload your interview recordings** — drop `.m4a`, `.mp3`, `.wav`, `.mp4`, or any common format into the **Upload Interview Recordings** field. Bulk uploads supported. 2. **Pick your options** — auto-detect language or pick from 99+, toggle speaker diarization to separate the interviewer from each guest, optionally translate non-English interviews to English. 3. **Run the actor** — recordings process 10 at a time in parallel on the paid tier; an entire project's interviews can be transcribed in one run. 4. **Download results** — every recording lands in the dataset with the transcript, segment + word-level timestamps, speaker labels, and ready-to-use SRT/VTT subtitle strings. Supported formats: M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM. Max 1 GB per file on the paid tier. --- ### Example output — interview transcript with speaker labels ```json { "transcript": "Interviewer: Tell me about the first time you realized... Guest: Honestly, it was when my mentor pulled me aside and said...", "detected_language": "en", "duration": 1432.7, "segments": [ { "id": 0, "text": "Tell me about the first time you realized you wanted to do this.", "start": 0.42, "end": 4.18, "speaker": "SPEAKER_00", "language": "en", "words": [ { "word": "Tell", "start": 0.42, "end": 0.61, "speaker": "SPEAKER_00" }, { "word": "me", "start": 0.61, "end": 0.74, "speaker": "SPEAKER_00" } ] }, { "id": 1, "text": "Honestly, it was when my mentor pulled me aside.", "start": 4.86, "end": 8.94, "speaker": "SPEAKER_01", "language": "en", "words": [] } ], "srt": "1\n00:00:00,420 --> 00:00:04,180\nTell me about the first time you realized you wanted to do this.\n\n2\n00:00:04,860 --> 00:00:08,940\nHonestly, it was when my mentor pulled me aside.", "vtt": "WEBVTT\n\n00:00:00.420 --> 00:00:04.180\nTell me about the first time you realized you wanted to do this.\n\n00:00:04.860 --> 00:00:08.940\nHonestly, it was when my mentor pulled me aside.", "speakers": ["SPEAKER_00", "SPEAKER_01"], "languages": ["en"], "fileSizeMB": 12.6, "success": true } ```` Every result includes the full transcript, segment-level timestamps, word-level timestamps, language detection, recording duration in seconds, file size, ready-to-use `srt` and `vtt` subtitle strings, and (when speaker diarization is enabled) speaker labels per segment and per word. *** ### Built for journalists, qualitative researchers, market researchers - 📰 **Journalists** — turn phone-recorded interviews into clean transcripts ready for quote pulling - 🧪 **Qualitative researchers** — preserve participant voices with speaker separation for thematic analysis - 📊 **Market researchers** — bulk-transcribe focus group and 1:1 interview tapes - 📚 **Oral historians** — searchable, time-stamped archives of long-form interviews - 🎙️ **Podcasters publishing interview shows** — transcripts for show notes, blog repurposing, and SEO *** ### Speaker diarization (interviewer / guest separation) Toggle the **Speaker Diarization** input and the actor automatically labels every segment and every word with the speaker it came from (`SPEAKER_00` for the interviewer, `SPEAKER_01` for the first guest, `SPEAKER_02` for the second, etc.). This makes it trivial to extract clean quote attributions for journalism or coding qualitative data for research. Powered by pyannote-audio. Charged per audio second; only billed when enabled. *** ### Translate foreign-language interviews to English Toggle **Translate to English** and the actor returns the transcript translated into English while preserving timing — perfect for conducting interviews in your subject's native language and publishing in English. Combine with **Speaker Diarization** to get clean, attributed quotes in both directions. Charged separately when enabled. *** ### SRT / VTT subtitle export Every transcription returns ready-to-use `srt` and `vtt` subtitle strings. Save the field value as a `.srt` or `.vtt` file and: - Publish a video version of the interview with subtitles for YouTube, Vimeo, or your CMS - Add HTML5 `` accessibility captions to embedded video - Build a searchable interview archive with timestamps Set **Timestamp Granularities** to `word` for cue precision down to individual words. *** ### Why interviewers choose this transcriber - ✅ **Interviewer ↔ guest separation** out of the box via pyannote-audio diarization — clean attributed quotes ready for publication - ⏱️ **Word-level timestamps** for every word — find any quote in a 90-minute interview in seconds - 🌐 **Translate non-English interviews** to English in the same run — perfect for international journalism and cross-cultural research - 🎬 **SRT and VTT subtitles included** for video versions of interviews - 🌍 **99+ languages** — automatic detection, no manual selection - 🇪🇺 **EU-region processing** for GDPR-aligned research workflows - 💰 **Pay per audio second** — no per-minute Rev.com markups, no Otter subscription - 🚀 **10× parallel** on the paid tier — an entire research project's worth of interviews done in one run *** ### Use cases - 📰 **Investigative journalists** transcribing source interviews and pulling attributed quotes for stories - 🎙️ **Long-form podcasters** generating publication-ready transcripts of every guest interview - 🧪 **Qualitative researchers** coding participant transcripts in NVivo, Atlas.ti, or MAXQDA - 📊 **Market research firms** transcribing focus groups and customer 1:1 sessions for thematic analysis - 📚 **Oral history projects** preserving long-form recorded interviews with timestamped speaker tracks - 🎓 **Academic researchers** conducting qualitative fieldwork in foreign-language contexts (transcribe + translate in one pass) - ✍️ **Authors and biographers** working from hours of recorded conversations for book material - 🎬 **Documentary filmmakers** preparing rough-cut transcripts of interview tape for editing *** ### Pricing & tiers Pay only for the audio seconds you actually transcribe. No subscriptions, no minimums. | FREE tier | PAID tier | |---|---| | Perfect for testing and small jobs | Built for production volume | | Up to 5 interviews per run | Unlimited interviews per run | | 50 MB max per file | 1 GB max per file | | 200 MB / 20 minutes monthly | Unlimited monthly volume | | 3 concurrent files | 10 concurrent files (10× parallel) | | No credit card required | $0.0005 per audio second | **Optional add-ons** (only billed when enabled): | Feature | Price | |---|---| | Speaker diarization | $0.0001 per audio second | | Translate to English | $0.0003 per audio second | | EU-region processing | $0.0007 per audio second (replaces base $0.0005) | A 60-minute interview with diarization on the paid tier costs approximately **$2.16** ($1.80 transcription + $0.36 diarization). Compare to Rev.com's $1.50/min ($90 for the same interview). *** ### Integration examples #### JavaScript / Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('sian.agency/transcribe-interview-to-text').call({ audioFiles: ['https://example.com/interview-with-source.m4a'], speakerDiarization: true, translateToEnglish: false, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items[0].transcript); console.log(items[0].srt); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient('YOUR_APIFY_TOKEN') run = client.actor('sian.agency/transcribe-interview-to-text').call(run_input={ 'audioFiles': ['https://example.com/interview-with-source.m4a'], 'speakerDiarization': True, 'translateToEnglish': False, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items[0]['transcript']) print(items[0]['vtt']) ``` #### cURL ```bash curl -X POST 'https://api.apify.com/v2/acts/sian.agency~transcribe-interview-to-text/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN' \ -H 'Content-Type: application/json' \ -d '{ "audioFiles": ["https://example.com/interview.m4a"], "speakerDiarization": true }' ``` #### n8n / Zapier / Make Wire this actor onto a "new file in research-recordings folder" trigger (Dropbox, Google Drive, OneDrive). The dataset record returned per item includes `transcript`, `segments[].words[]`, `srt`, and `vtt` — drop them into Notion (research database), Airtable (interview log), MAXQDA/NVivo (qualitative coding), or Google Docs (story drafts). *** ### FAQ **How accurate is interview transcription?** Powered by an industrial speech-to-text pipeline tuned for natural conversation. Accuracy is typically 95–99% on clean studio or quiet-room interviews, lower on phone-recorded or noisy field interviews. Word-level timestamps are returned even when accuracy is imperfect, so you can verify and correct quote attributions quickly. **What audio and video formats are supported?** M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM. Max 50 MB per file on the free tier, 1 GB on the paid tier. **Can I transcribe foreign-language interviews?** Yes — auto-detection across 99+ languages including Spanish, French, German, Mandarin, Japanese, Portuguese, Arabic, Hindi, Russian, and many more. Toggle **Translate to English** to receive an English transcript alongside the timestamped original. **Is speaker diarization included?** Yes, opt-in via the **Speaker Diarization** toggle. Each segment and word gets labeled `SPEAKER_00` (interviewer), `SPEAKER_01` (first guest), etc. Powered by pyannote-audio. Billed at $0.0001 per audio second only when enabled. **How does pricing work?** Pay-per-audio-second. The free tier covers small jobs and testing without a credit card. The paid tier is $0.0005 per second of audio. A 1-hour interview with diarization is approximately $2.16 — versus Rev.com at ~$90 for the same length. **Can I integrate this into my qualitative research workflow?** Yes. The actor exposes a standard Apify run/dataset API. The dataset record includes `transcript`, `segments[].words[]`, `srt`, and `vtt` ready to feed into NVivo, MAXQDA, Atlas.ti, Dovetail, or any qualitative analysis tool that accepts plain text or VTT. **What if my interview is multi-speaker (panel, focus group)?** Speaker diarization handles up to ~6 distinct speakers reliably. Each speaker is labeled `SPEAKER_00` through `SPEAKER_N` in temporal order of first speaking turn. **How long does a transcription take?** A 60-minute interview takes 1–3 minutes on the paid tier. Bulk batches of 10 interviews complete in 5–10 minutes (parallelized). *** ### Legal disclaimer Use this actor only on interviews you have rights to transcribe — your own recordings with subject consent, properly licensed media, or material covered by journalistic source agreements. Some jurisdictions require subject consent for recording; you are responsible for compliance with applicable laws and IRB requirements for academic research. The actor does not retain audio or transcripts beyond the run's lifetime. **EU-region processing** is available via the EU Processing toggle for GDPR-aligned workflows. SIÁN Agency provides this actor as-is. *** ### Support [![Telegram Support](https://img.shields.io/badge/Telegram-Support%20Group-0088cc?logo=telegram)](https://t.me/+vyh1sRE08sAxMGRi) [![Email](https://img.shields.io/badge/Email-support%40sian--agency.online-EA4335)](mailto:support@sian-agency.online) [![SIÁN Agency](https://img.shields.io/badge/Store-SI%C3%81N%20Agency-97cc64)](https://apify.com/sian.agency?fpr=sian) Join the Telegram support group, email **support@sian-agency.online**, or open an issue on the [SIÁN Agency Apify Store](https://apify.com/sian.agency?fpr=sian) page. *** ### More from SIÁN Agency Platform-specific scrapers + transcribers: - [Instagram AI Transcript Extractor](https://apify.com/sian.agency/instagram-ai-transcript-extractor?fpr=sian) - [Best TikTok AI Transcript Extractor](https://apify.com/sian.agency/best-tiktok-ai-transcript-extractor?fpr=sian) - [YouTube Shorts AI Transcript Extractor](https://apify.com/sian.agency/youtube-shorts-ai-transcript-and-metadata-extractor?fpr=sian) - [Facebook AI Transcript Extractor](https://apify.com/sian.agency/facebook-ai-transcript-extractor?fpr=sian) Browse the full [SIÁN Agency Apify Store](https://apify.com/sian.agency?fpr=sian) for all available actors. *** # Actor input Schema ## `audioFiles` (type: `array`): Upload your interview recordings directly. Most journalists and researchers record locally — drop the files in here without having to host them anywhere first. **Supported Formats:** M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM **Max file size:** 1GB per file You can also paste hosted URLs in the optional **Interview Recording URLs** field below. ## `audioUrls` (type: `array`): Optional: add direct interview audio/video URLs (one per line) if your recordings are already hosted somewhere (Dropbox direct link, your CDN, archive.org, etc.). 🚫 **Social media links are rejected** — use the specialized actors linked in the description. ✅ **Valid:** `https://example.com/interview.mp3`, `https://cdn.example.com/oral-history.wav` **Supported Formats:** M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM ## `language` (type: `string`): Language spoken in the audio. Leave as 'Auto-detect' for automatic language detection. ## `translateToEnglish` (type: `boolean`): Translate non-English audio into English. Additional charges apply for translation service. ## `useEuServers` (type: `boolean`): Process data within the EU for GDPR compliance. Higher processing rates apply for EU servers. ## `speakerDiarization` (type: `boolean`): Identify and label different speakers in the audio (e.g., SPEAKER\_00, SPEAKER\_01). Perfect for meetings, interviews, and multi-person conversations. Additional charges apply. ## Actor input object example ```json { "audioUrls": [ "https://raw.githubusercontent.com/rara-cyber/podcast-test-file/main/KchSfOdwCJE-56eb7ccd6dc030fa3cc280ab26925c4e234.opus" ], "language": "auto", "translateToEnglish": false, "useEuServers": false, "speakerDiarization": false } ``` # Actor output Schema ## `audioTranscripts` (type: `string`): Processed transcription data with timestamps, speaker diarization, detected languages, and file metadata ## `scrapingSummary` (type: `string`): HTML summary showing successful and failed transcriptions with key metrics # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "audioUrls": [ "https://raw.githubusercontent.com/rara-cyber/podcast-test-file/main/KchSfOdwCJE-56eb7ccd6dc030fa3cc280ab26925c4e234.opus" ] }; // Run the Actor and wait for it to finish const run = await client.actor("sian.agency/transcribe-interview-to-text").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "audioUrls": ["https://raw.githubusercontent.com/rara-cyber/podcast-test-file/main/KchSfOdwCJE-56eb7ccd6dc030fa3cc280ab26925c4e234.opus"] } # Run the Actor and wait for it to finish run = client.actor("sian.agency/transcribe-interview-to-text").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "audioUrls": [ "https://raw.githubusercontent.com/rara-cyber/podcast-test-file/main/KchSfOdwCJE-56eb7ccd6dc030fa3cc280ab26925c4e234.opus" ] }' | apify call sian.agency/transcribe-interview-to-text --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=sian.agency/transcribe-interview-to-text", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Transcribe Interview to Text — for Journalists & Researchers", "description": "Transcribe interviews and recorded conversations to text. Speaker labels for interviewer and guest, word-level timestamps, SRT/VTT. Try free.", "version": "1.0", "x-build-id": "pT468U8fC6pC5PiLH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/sian.agency~transcribe-interview-to-text/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-sian.agency-transcribe-interview-to-text", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/sian.agency~transcribe-interview-to-text/runs": { "post": { "operationId": "runs-sync-sian.agency-transcribe-interview-to-text", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/sian.agency~transcribe-interview-to-text/run-sync": { "post": { "operationId": "run-sync-sian.agency-transcribe-interview-to-text", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "audioFiles": { "title": "Upload Interview Recordings", "type": "array", "description": "Upload your interview recordings directly. Most journalists and researchers record locally — drop the files in here without having to host them anywhere first.\n\n**Supported Formats:** M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM\n**Max file size:** 1GB per file\n\nYou can also paste hosted URLs in the optional **Interview Recording URLs** field below." }, "audioUrls": { "title": "Interview Recording URLs (optional)", "type": "array", "description": "Optional: add direct interview audio/video URLs (one per line) if your recordings are already hosted somewhere (Dropbox direct link, your CDN, archive.org, etc.).\n\n🚫 **Social media links are rejected** — use the specialized actors linked in the description.\n\n✅ **Valid:** `https://example.com/interview.mp3`, `https://cdn.example.com/oral-history.wav`\n\n**Supported Formats:** M4A, MP3, WAV, FLAC, AAC, OPUS, OGG, MP4, MOV, WebM", "items": { "type": "string" } }, "language": { "title": "Language (Optional)", "enum": [ "auto", "english", "chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese", "cantonese" ], "type": "string", "description": "Language spoken in the audio. Leave as 'Auto-detect' for automatic language detection.", "default": "auto" }, "translateToEnglish": { "title": "🔄 Translate to English (PAID)", "type": "boolean", "description": "Translate non-English audio into English. Additional charges apply for translation service.", "default": false }, "useEuServers": { "title": "🇪🇺 EU-Based Processing (PAID)", "type": "boolean", "description": "Process data within the EU for GDPR compliance. Higher processing rates apply for EU servers.", "default": false }, "speakerDiarization": { "title": "🎤 Speaker Diarization (PAID)", "type": "boolean", "description": "Identify and label different speakers in the audio (e.g., SPEAKER_00, SPEAKER_01). Perfect for meetings, interviews, and multi-person conversations. Additional charges apply.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```