YouTube Transcript Enhanced

Extract YouTube transcripts with SRT/VTT subtitle export, paragraph chunking, keyword search, time range filtering, and text analytics. Works with any public YouTube video.

What does YouTube Transcript Enhanced do?

YouTube Transcript Enhanced extracts transcripts from YouTube videos and adds powerful post-processing features. Beyond raw transcript segments, it provides ready-to-use subtitle files (SRT/VTT), intelligent paragraph grouping, keyword search across the transcript, time range filtering, and text analysis with word counts and keyword extraction.

It uses YouTube's public InnerTube API to access caption tracks — the same API YouTube's own player uses. Both manual captions and auto-generated subtitles are supported across 100+ languages.

Why use YouTube Transcript Enhanced?

• Multiple output formats — Export as SRT subtitles, VTT subtitles, timestamped plain text, or JSON segments
• Paragraph chunking — Groups small caption segments into coherent paragraphs using pause detection
• Keyword search — Find specific content in transcripts with timestamp references
• Time range filtering — Extract only the portion of the transcript you need
• Text analytics — Word count, reading time, unique words, and top keyword extraction
• Full metadata — Video title, channel, views, duration, keywords, thumbnail, publish date
• Batch processing — Process multiple videos in a single run
• Language selection — Choose preferred language with smart fallback logic

Use cases

• Content repurposing — Convert video transcripts into blog posts, articles, or social media content
• Subtitle generation — Get SRT/VTT files for videos that lack proper subtitles
• Research — Search transcripts for specific topics or keywords across multiple videos
• SEO analysis — Extract keywords and topics from video content
• Accessibility — Generate formatted transcripts for hearing-impaired users
• Education — Extract and chunk lecture transcripts into study materials

Input parameters

Parameter	Type	Required	Default	Description
urls	string[]	Yes	—	YouTube video URLs or 11-character video IDs
language	string	No	en	ISO 639-1 language code for preferred transcript
includeAutoGenerated	boolean	No	true	Allow auto-generated captions as fallback
outputFormat	string	No	json	Output format: json, srt, vtt, or text
chunkParagraphs	boolean	No	false	Group segments into paragraphs
searchKeywords	string	No	—	Comma-separated keywords to search in transcript
timeRangeStart	integer	No	—	Start time in seconds for time range filter
timeRangeEnd	integer	No	—	End time in seconds for time range filter
includeTextAnalysis	boolean	No	true	Include word count, reading time, top keywords

Output example

{
    "videoId": "jNQXAC9IVRw",
    "videoUrl": "https://www.youtube.com/watch?v=jNQXAC9IVRw",
    "videoTitle": "Me at the zoo",
    "channelName": "jawed",
    "language": "en",
    "isAutoGenerated": true,
    "segmentCount": 5,
    "fullText": "All right so here we are...",
    "srt": "1\n00:00:01,000 --> 00:00:04,000\nAll right so here we are...",
    "paragraphs": [
        {
            "text": "All right so here we are in front of the elephants...",
            "startTime": 1.0,
            "endTime": 12.5,
            "segmentCount": 3
        }
    ],
    "paragraphCount": 2,
    "textAnalysis": {
        "wordCount": 42,
        "uniqueWordCount": 30,
        "characterCount": 210,
        "readingTimeMinutes": 0.2,
        "topKeywords": [
            { "word": "elephants", "count": 2 },
            { "word": "cool", "count": 2 }
        ]
    },
    "wordCount": 42,
    "readingTimeMinutes": 0.2,
    "enrichedAt": "2026-03-01T12:00:00.000Z"
}

Output formats explained

Format	Description	Output field
json	Raw transcript segments with start time and duration	segments array (always included)
srt	SubRip subtitle format, ready to use with video players	srt string
vtt	WebVTT subtitle format, compatible with HTML5 video	vtt string
text	Plain text with [MM:SS] timestamps per line	formattedText string

Enhancement features

Paragraph chunking

When chunkParagraphs is enabled, the actor groups small segments into paragraphs based on natural pause detection (gaps > 1.5 seconds between segments). Each paragraph includes start/end times and the merged text.

Keyword search

Set searchKeywords to a comma-separated list (e.g., "AI, machine learning, neural") to search the transcript. Returns matching segments with the keyword that triggered the match and the timestamp.

Time range filtering

Use timeRangeStart and timeRangeEnd (in seconds) to extract only a portion of the transcript. For example, timeRangeStart: 60, timeRangeEnd: 300 extracts minutes 1-5 only.

Text analysis

When includeTextAnalysis is enabled, the output includes word count, unique word count, character count, estimated reading time (~200 WPM), and the top 20 most frequent meaningful keywords (stop words excluded).

How much does it cost?

YouTube Transcript Enhanced uses pay-per-event pricing:

Event	Price	Description
Actor start	$0.035	Charged once per run
Transcript enriched	$0.005	Charged per successfully enriched transcript

Example costs:

• 1 video: $0.035 + $0.005 = $0.04
• 10 videos: $0.035 + (10 x $0.005) = $0.085
• 100 videos: $0.035 + (100 x $0.005) = $0.535

Using the Apify API

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('YOUR_ACTOR_ID').call({
    urls: ['https://www.youtube.com/watch?v=dQw4w9WgXcQ'],
    outputFormat: 'srt',
    chunkParagraphs: true,
    includeTextAnalysis: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.log(`${item.videoTitle} — ${item.wordCount} words, ${item.readingTimeMinutes} min read`);
    console.log(`Top keywords: ${item.textAnalysis.topKeywords.map(k => k.word).join(', ')}`);
    // Save SRT file
    if (item.srt) fs.writeFileSync(`${item.videoId}.srt`, item.srt);
});

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("YOUR_ACTOR_ID").call(run_input={
    "urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "outputFormat": "srt",
    "chunkParagraphs": True,
    "includeTextAnalysis": True,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['videoTitle']} — {item['wordCount']} words")
    # Save SRT file
    if item.get("srt"):
        with open(f"{item['videoId']}.srt", "w") as f:
            f.write(item["srt"])

Integrations

• Google Sheets — Export transcript data and analytics to spreadsheets
• Webhooks — Get notified when transcript extraction completes
• Zapier / Make — Automate workflows triggered by new transcripts
• Other Apify actors — Chain with scrapers that collect YouTube URLs

Tips and best practices

• Use outputFormat: "srt" or "vtt" when you need subtitle files for video editing
• Enable chunkParagraphs for content repurposing — paragraphs are easier to read than raw segments
• Use searchKeywords to quickly find relevant sections in long videos
• Time range filtering is useful for extracting specific sections from lectures or interviews
• The fullText field is always included and ready for further text processing
• For batch processing, all videos share the same settings — use separate runs for different configurations

Compliance

This actor uses YouTube's public InnerTube API to access caption tracks — the same API used by YouTube's own video player. It accesses only publicly available video metadata and captions. No login credentials or private data are used.