# Instagram Reel Transcript Extractor 📸 (`scriptbase/instagram-reel-transcript-extractor`) Actor 📸 Convert any Instagram Reel to text. Extract the transcript and subtitles with timestamps. Outputs JSON, SRT, or plain text. Auto-captions + speech-to-text fallback. 14+ languages. No login needed. - **URL**: https://apify.com/scriptbase/instagram-reel-transcript-extractor.md - **Developed by:** [Scriptbase](https://apify.com/scriptbase) (community) - **Categories:** AI, Social media, Automation - **Stats:** 6 total users, 5 monthly users, 91.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Instagram Reel Transcript Extractor Extract transcripts from Instagram Reels — the short-form vertical videos at the center of Instagram's discovery algorithm. Purpose-built for the Reels format: paste a Reel URL and get back timestamped text for hook extraction, creator research, and automated captioning workflows. Works with any public Instagram Reel. No login required. ### What it does 1. You provide an Instagram Reel URL (`/reel/` or `/reels/`). 2. The actor extracts the spoken transcript with precise timestamps. 3. You get back structured text in JSON, plain text, SRT, or WebVTT — optimized for creator analysis, caption generation, and competitive research. Unlike the general Instagram transcript actor (which also covers IGTV and feed video posts), this actor is purpose-built for Reels. Its accepted URL set is intentionally narrow so your pipeline stays focused on short-form Reels content specifically. ### Key features - **Reels-specific** — accepts only `/reel/` and `/reels/` URLs, eliminating noise from other content types. - **Hook & script extraction** — Reels are won or lost in the first two seconds. Get timestamped text to study what hooks appear in viral content at scale. - **Caption-ready output** — export SRT or WebVTT directly usable in mobile editors (CapCut, DaVinci Resolve, Premiere) or Instagram's own caption feature. - **Timestamped segments** — every phrase has a `start` and `end` time for frame-accurate caption placement. - **4 output formats** — JSON with timestamps, plain text, SRT, or WebVTT. - **Multi-language** — uses Instagram's caption data when present; speech-to-text fallback covers 14 languages. - **No login required.** ### Supported languages When Instagram provides caption data for the Reel, the actor extracts it in the source language. When captions are absent, speech-to-text fallback supports: | Code | Language | |------|----------| | `en` | English | | `es` | Spanish | | `fr` | French | | `de` | German | | `pt` | Portuguese | | `it` | Italian | | `nl` | Dutch | | `ja` | Japanese | | `ko` | Korean | | `zh` | Chinese | | `ar` | Arabic | | `ru` | Russian | | `tr` | Turkish | | `hi` | Hindi | ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `url` | string | *(required)* | Instagram Reel URL | | `language` | string | `"en"` | Preferred language ([ISO 639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes)) | | `format` | string | `"json"` | `"json"`, `"text"`, `"srt"`, or `"vtt"` | #### Supported URLs ```` https://www.instagram.com/reel/ABC123DEF456/ https://www.instagram.com/reels/ABC123DEF456/ ```` Only Reel URLs are accepted. Instagram feed posts (`/p/`) or IGTV (`/tv/`) are not supported by this actor — use the Instagram Transcript Extractor for those formats. ### Output example When `format` is `json`, each dataset row looks like this: ```json { "url": "https://www.instagram.com/reel/ABC123DEF456/", "platform": "instagram", "language": "en", "duration_sec": 29, "segments": [ { "start": 0.0, "end": 2.4, "text": "Stop scrolling. This productivity hack will save you two hours every day." }, { "start": 2.4, "end": 6.0, "text": "All you need is a timer and the right task order." } ], "full_text": "Stop scrolling. This productivity hack will save you two hours every day. All you need is a timer and the right task order." } ```` When `format` is `text`, `srt`, or `vtt`, the formatted transcript is written to the actor's key-value store under the `OUTPUT` key. When extraction fails, the dataset row contains a clear error: ```json { "error": "NOT_FOUND", "message": "The video is private, removed, or has no extractable transcript." } ``` ### Error codes | Code | Meaning | |------|---------| | `INVALID_FORMAT` | `format` was not one of json/text/srt/vtt | | `BAD_REQUEST` | The URL was malformed or rejected by the transcript operation | | `UNSUPPORTED_PLATFORM` | No transcript operation serves this URL's platform | | `UNAUTHORIZED` | The actor's ScriptBase key is missing, invalid, or revoked | | `INSUFFICIENT_CREDITS` | The ScriptBase account behind this actor is out of credits | | `NOT_FOUND` | The video is private, removed, or has no extractable transcript | | `UPSTREAM_FAILED` | Every transcript source failed -- retry shortly | | `RATE_LIMITED` | Too many requests -- retry after a short delay | | `TIMEOUT` | Extraction took longer than the actor's poll budget | | `INTERNAL_ERROR` | Unexpected error during extraction | ### Use cases - **Hook analysis** — extract opening lines from viral Reels at scale to reverse-engineer what makes audiences stop scrolling. Build a personal swipe file or train an LLM on high-performing Reel scripts. - **Creator & competitor research** — transcribe the Reels of top creators in your niche without watching each one. Identify recurring frameworks, CTAs, and topic patterns. - **Automated captioning** — generate SRT or WebVTT for your own Reels to boost accessibility and increase average watch time. Studies show captions reduce drop-off on silent autoplay. - **Multilingual repurposing** — get clean source text from a Reel and feed it into a translation API to produce captions in multiple languages for international audiences. - **Social listening** — monitor what brands and influencers are saying in Reel content. Feed transcripts into sentiment analysis or topic-modeling pipelines. - **Content brief generation** — automatically convert a competitor's top Reels into written outlines that inform your own content calendar. ### Integrations Use this actor through the [Apify API](https://docs.apify.com/api/v2) or wire it into your creator tool stack: - **Python** — `apify_client.actor("your-actor-id").call(run_input={"url": "https://www.instagram.com/reel/ABC123DEF456/"})` - **JavaScript** — `await client.actor("your-actor-id").call({url: "https://www.instagram.com/reel/ABC123DEF456/"})` - **Zapier / Make / n8n** — pair this with an Instagram scraper to build a fully automated pipeline: discover Reels → extract transcripts → store in Notion or Airtable. - **Webhooks** — fire a webhook when the transcript is ready, triggering summarization, translation, or publishing automation. ### FAQ **Does this work with regular Instagram posts or only Reels?** Only Reels (`/reel/` and `/reels/` URLs). For feed posts or IGTV, use the Instagram Transcript Extractor. **Does it need an Instagram account?** No. The actor works with any publicly accessible Reel without credentials or cookies. **What if the Reel uses music with no speech?** Music-only Reels have no spoken transcript. The actor returns a `NOT_FOUND` error for content with no extractable speech. **My Reel has no Instagram captions — will speech-to-text work?** Yes. When captions are missing, the actor applies speech-to-text extraction. See the [supported languages](#supported-languages) table for coverage. **Can I process a whole list of Reel URLs in one job?** Use the Apify API to loop over an array of URLs, or use a Make/n8n scenario with a data iterator. **What does it cost?** Pricing is per transcribed minute (1 minute = 1 charge unit, minimum 1), so you pay only for the audio actually processed — and failed extractions cost nothing. The exact per-minute price is shown on this actor's Apify Store page. # Actor input Schema ## `url` (type: `string`): URL of the Instagram Reel. ## `language` (type: `string`): Preferred transcript language as an ISO 639-1 code (e.g. en, es, fr, de, ja). ## `format` (type: `string`): Choose how the transcript is returned. JSON includes timestamps per segment. Text returns the full transcript as a plain string. SRT and VTT are subtitle file formats. ## Actor input object example ```json { "url": "https://www.instagram.com/reel/DWoej6aDOaE", "language": "en", "format": "json" } ``` # Actor output Schema ## `overview` (type: `string`): No description ## `segments` (type: `string`): No description # 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 = { "url": "https://www.instagram.com/reel/DWoej6aDOaE", "language": "en", "format": "json" }; // Run the Actor and wait for it to finish const run = await client.actor("scriptbase/instagram-reel-transcript-extractor").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 = { "url": "https://www.instagram.com/reel/DWoej6aDOaE", "language": "en", "format": "json", } # Run the Actor and wait for it to finish run = client.actor("scriptbase/instagram-reel-transcript-extractor").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 '{ "url": "https://www.instagram.com/reel/DWoej6aDOaE", "language": "en", "format": "json" }' | apify call scriptbase/instagram-reel-transcript-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scriptbase/instagram-reel-transcript-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Reel Transcript Extractor 📸", "description": "📸 Convert any Instagram Reel to text. Extract the transcript and subtitles with timestamps. Outputs JSON, SRT, or plain text. Auto-captions + speech-to-text fallback. 14+ languages. No login needed.", "version": "0.1", "x-build-id": "wKGHEnOi0iLe4SAwq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scriptbase~instagram-reel-transcript-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scriptbase-instagram-reel-transcript-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scriptbase~instagram-reel-transcript-extractor/runs": { "post": { "operationId": "runs-sync-scriptbase-instagram-reel-transcript-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scriptbase~instagram-reel-transcript-extractor/run-sync": { "post": { "operationId": "run-sync-scriptbase-instagram-reel-transcript-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "url" ], "properties": { "url": { "title": "Instagram Reel URL", "type": "string", "description": "URL of the Instagram Reel." }, "language": { "title": "Language", "type": "string", "description": "Preferred transcript language as an ISO 639-1 code (e.g. en, es, fr, de, ja).", "default": "en" }, "format": { "title": "Output Format", "enum": [ "json", "text", "srt", "vtt" ], "type": "string", "description": "Choose how the transcript is returned. JSON includes timestamps per segment. Text returns the full transcript as a plain string. SRT and VTT are subtitle file formats.", "default": "json" } } }, "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 } } } } } } } } } } ```