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Automated SRT and VTT Video Captions (April 2020 Update)

This month we added new acoustic models for UK customers, automated video captioning (SRT/VTT), and automatic transcript summaries.

Now, companies in industries like video hosting, media monitoring, e-discovery, or video interviewing will be able to improve video playback and search for their customers!

New Acoustic Model for UK accented English audio/video

State-of-the-Art accuracy is now available for UK accented English with just a quick change to your acoustic model parameter.

Default Model: assemblyai_default

UK Model: assemblyai_en_uk

Check out all of our acoustic and language models in our API docs here.

Automated Video Captioning: SRT or VTT export

You can easily export your transcription in SRT or VTT format, to be plugged into a video player for subtitles and closed captions.

Once your transcript status shows as "completed", you can make a GET request to the following endpoints to export your transcript in VTT or SRT format:

https://api.assemblyai.com/v2/transcript/<your transcript id>/vtt
https://api.assemblyai.com/v2/transcript/<your transcript id>/srt

The API will output a plain-text response like this (SRT example):

1
00:00:12,340 --> 00:00:16,380
Last year I showed these two slides said that demonstrate that

2
00:00:16,340 --> 00:00:19,920
the Arctic ice cap which for most of the last 3,000,000 years has been

3
00:00:19,880 --> 00:00:23,120
the size of the lower 48 States has shrunk by 40%

...

Take a look at our API docs to learn more about automatically exporting a transcript in SRT or VTT format here.

Automatic Transcript Highlights

Many of our customers with long forms of audio and video files (e.g. webinars, podcasts, conference calls, video interviews) were looking for ways to make their transcriptions easier to review more quickly. In addition, they wanted to be able to tag these calls immediately depending on the most important key phrases.

That's where auto transcript highlights come in. We can now detect key phrases in your transcripts using Natural Language Processing (NLP) to help with features like:

  • Summarize transcription text: Simplify long transcriptions to only highlight the most common keywords and phrases
  • Auto-tagging/indexing: Make your entire file searchable by adding in auto-highlights to each file as a searchable tag

Example transcript
Hi I'm joy. Hi I'm Sharon. Do you have kids in school? I have grandchildren in school. Okay, well, my kids are in middle school in high school. Do you think there is anything wrong with the school system? Overcrowding, of course,...
Auto highlights
"high school"
"middle school"
"kids"

Below is a code snippet of how to turn on automatic transcript highlights in Python, for snippets of code in other languages, click here.

import requests

endpoint = "https://api.assemblyai.com/v2/transcript"

json = {
  "audio_url": "https://app.assemblyai.com/static/media/phone_demo_clip_1.wav",
  "auto_highlights": True
}

headers = {
    "authorization": "YOUR-API-TOKEN",
    "content-type": "application/json"
}

response = requests.post(endpoint, json=json, headers=headers)

print(response.json())

100% Uptime

Another month of 100% uptime across all our models, subscribe to our status page to stay up-to-date!

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