Transcription Guide

FastDrop’s /transcribe endpoint handles speech-to-text, language detection, English translation, and subtitle file generation in a single API call. This guide explains the pipeline, how to get the best results, and common integration patterns.

How it works

When you submit a video to /transcribe, FastDrop runs a multi-step pipeline:

Audio extraction — The audio track is extracted from your video file
Language detection — The spoken language is automatically identified (or uses your language hint)
Transcription — Speech is converted to text with word-level and segment-level timestamps
Translation — If the source language isn’t English and translate is true, a full English translation is generated
File generation — If output_formats is specified, SRT and/or TXT subtitle files are generated and uploaded

The entire pipeline runs asynchronously. You submit the job and either receive a webhook or fetch the result with ?wait=N. See Getting your results.

Response modes

JSON only (default)

When you don’t specify output_formats, you get a structured JSON response with the full transcript, segments, word-level timestamps, and (if applicable) an English translation. This is ideal for:

Indexing transcripts for search
Extracting quotes or key moments
Building custom UI around transcript data
Feeding transcripts into downstream processing

curl -X POST https://api.fastdrop.io/api/v1/transcribe \
  -H "Content-Type: application/json" \
  -H "X-API-Key: fd_live_your_key_here" \
  -d '{"video_url": "https://example.com/video.mp4"}'

With subtitle files

Pass output_formats to generate downloadable subtitle files alongside the JSON response. This is ideal for:

Adding captions to video players
Importing subtitles into editing software (Premiere, DaVinci, Final Cut)
Delivering accessible video content
Archiving transcripts as standalone files

curl -X POST https://api.fastdrop.io/api/v1/transcribe \
  -H "Content-Type: application/json" \
  -H "X-API-Key: fd_live_your_key_here" \
  -d '{
    "video_url": "https://example.com/video.mp4",
    "output_formats": ["srt", "txt"]
  }'

Available formats:

Format	Description
`srt`	SubRip subtitle format with timestamps. Compatible with most video players and editors.
`txt`	Plain text transcript without timestamps. Useful for reading, archiving, or text processing.

When translation is performed, you get both source-language and English files:

source_srt / source_txt — Transcript in the original language
english_srt / english_txt — English translation (only for non-English sources)

File download URLs are presigned and expire after 1 hour. Download or store them immediately after receiving results.

Language detection vs. language hints

Auto-detection

By default, FastDrop detects the spoken language from the audio. This works well for high-accuracy languages but can struggle with lower-resource languages that sound similar to a higher-resource one.

Using the `language` parameter

Passing a language hint bypasses detection entirely. This is recommended when:

You already know the language (e.g., from user input or metadata)
You’re working with a medium or low-accuracy language
You’re processing a batch of videos in the same language
Detection is returning the wrong language

{
  "video_url": "https://example.com/swahili-interview.mp4",
  "language": "sw"
}

See Supported Languages for all valid ISO 639-1 codes.

Translation

When the source language is not English and translate is true (the default), FastDrop generates a full English translation. The translation:

Preserves segment-level timestamps from the original transcription
Is generated from the transcribed text, not directly from audio
Works across all 99 supported languages

Disabling translation

If you only need the source-language transcript, set translate to false to skip the translation step. This doesn’t reduce the credit cost but slightly speeds up processing.

{
  "video_url": "https://example.com/video.mp4",
  "translate": false
}

English source videos

When the detected (or specified) language is English, no translation is performed regardless of the translate setting. The translation field will be absent from the response.

Timestamps

FastDrop returns two levels of timing data:

Segments

Sentence-level chunks with start and end times. These map naturally to subtitle lines:

{
  "segments": [
    { "start": 0.0, "end": 2.8, "text": "Welcome to the show." },
    { "start": 3.1, "end": 8.5, "text": "Today we're going to talk about video editing." }
  ]
}

Words

Individual word timestamps for precise alignment. Useful for karaoke-style captions or precise text-to-video sync:

{
  "words": [
    { "start": 0.0, "end": 0.5, "word": "Welcome" },
    { "start": 0.5, "end": 0.7, "word": "to" },
    { "start": 0.7, "end": 0.9, "word": "the" },
    { "start": 0.9, "end": 1.3, "word": "show." }
  ]
}

Word-level timestamps are available for the source transcription only. Translated text uses segment-level timestamps carried over from the source.

Accuracy considerations

Transcription accuracy varies by language. FastDrop classifies languages into three tiers based on training data availability:

Tier	WER range	Languages
High	Under 8%	English, Spanish, French, German, Japanese, and 25 more
Medium	8–15%	Bengali, Tamil, Swahili, Persian, Welsh, and 30 more
Low	15–40%+	Amharic, Yoruba, Hausa, Hawaiian, Tibetan, and 28 more

See Supported Languages for the complete breakdown.

Factors that affect accuracy

Beyond language tier, these factors influence transcription quality:

Audio quality — Clear audio with minimal background noise produces the best results
Speaker clarity — Single speakers with clear enunciation transcribe better than overlapping speakers
Domain vocabulary — Technical, medical, or domain-specific terms may be misrecognized
Accents and dialects — Strong regional accents or dialectal variation can reduce accuracy, especially for languages marked as “high accuracy” based on their standard form

Common workflows

Subtitles for multilingual content

{
  "video_url": "https://example.com/arabic-interview.mp4",
  "output_formats": ["srt"]
}

Returns both source_srt (Arabic) and english_srt (English translation) ready to import into any video editor.

Search indexing

{
  "video_url": "https://example.com/podcast.mp4"
}

Use the text field to index the full transcript for search. The segments field lets you link search results to specific timestamps.

Batch transcription

Use the batch endpoint to transcribe up to 50 videos at once. Each video in the batch can include transcribe as a capability alongside other capabilities like classify or thumbnails.

Combine with classification

Request transcription alongside classification in a single job:

{
  "video_url": "https://example.com/footage.mp4",
  "capabilities": ["classify", "transcribe", "thumbnails"],
  "processing_tier": "basic"
}

This costs 2 (classify) + 8 (transcribe) + 1 (thumbnails) = 11 credits and runs all capabilities in parallel.

Get Started

Understanding video defects

Guides

Transcription Guide

How it works

Response modes

JSON only (default)

With subtitle files

Language detection vs. language hints

Auto-detection

Using the `language` parameter

Translation

Disabling translation

English source videos

Timestamps

Segments

Words

Accuracy considerations

Factors that affect accuracy

Common workflows

Subtitles for multilingual content

Search indexing

Batch transcription

Combine with classification

​How it works

​Response modes

​JSON only (default)

​With subtitle files

​Language detection vs. language hints

​Auto-detection

​Using the language parameter

​Translation

​Disabling translation

​English source videos

​Timestamps

​Segments

​Words

​Accuracy considerations

​Factors that affect accuracy

​Common workflows

​Subtitles for multilingual content

​Search indexing

​Batch transcription

​Combine with classification

How it works

Response modes

JSON only (default)

With subtitle files

Language detection vs. language hints

Auto-detection

Using the `language` parameter

Translation

Disabling translation

English source videos

Timestamps

Segments

Words

Accuracy considerations

Factors that affect accuracy

Common workflows

Subtitles for multilingual content

Search indexing

Batch transcription

Combine with classification