This package is the Python implementation of Deepgram's WebVTT and SRT formatting. Given a transcription, this package can return a valid string to store as WebVTT or SRT caption files.
The package is not dependent on Deepgram, but it is expected that you will provide a JSON response from a transcription request from either Deepgram or one of the other supported speech-to-text APIs.
pip install deepgram-captionsThe converter takes in a JSON object response (see examples in the ./test folder.) Depending on which API you use, the converter will turn that into a shape that can be handled by the webvtt and srt scripts.
You provide the JSON object; then select the converter needed such as DeepgramConverter, WhisperTimestampedConverter, AssemblyAIConverter and so on. (If the API you want to use is not supported, please reach out to [email protected] and we will do our best to add it.)
from deepgram_captions import DeepgramConverter, webvtt
transcription = DeepgramConverter(dg_response)
captions = webvtt(transcription)from deepgram_captions import DeepgramConverter, srt
transcription = DeepgramConverter(dg_response)
captions = srt(transcription)Add an optional integer parameter to set the line length of the caption.
line_length = 10
deepgram = DeepgramConverter(dg_speakers)
captions = webvtt(deepgram, line_length)Open AI's Whisper (through their API) does not provide timestamps, so a JSON response directly from OpenAI cannot be used with this package. However, there are a couple other options you can try:
Use Deepgram's fully hosted Whisper Cloud, which gives you Whisper transcriptions along with the features that come with Deepgram's API such as timestamps. Use model=whisper when you make your request to Deepgram. Then use the DeepgramConverter to create the captions.
from deepgram_captions import DeepgramConverter, srt
transcription = DeepgramConverter(whisper_response)
captions = srt(transcription)Whisper Timestamped adds word-level timestamps to OpenAI's Whisper speech-to-text transcriptions. Word-level timestamps are required for this package to create captions, which is why we have created the captions converter for Whisper Timestamped (and not OpenAI's Whisper).
from deepgram_captions import WhisperTimestampedConverter, webvtt
transcription = WhisperTimestampedConverter(whisper_response)
captions = webvtt(transcription)AssemblyAI is another popular speech-to-text API.
from deepgram_captions import AssemblyAIConverter, webvtt
transcription = AssemblyAIConverter(assembly_response)
captions = webvtt(transcription)When transcribing https://dpgr.am/spacewalk.wav, and running it through our library, this is the WebVTT output.
from deepgram_captions.converters import DeepgramConverter
from deepgram_captions.webvtt import webvtt
transcription = DeepgramConverter(dg_response)
captions = webvtt(transcription)
print(captions)This is the result:
WEBVTT
NOTE
Transcription provided by Deepgram
Request Id: 686278aa-d315-4aeb-b2a9-713615544366
Created: 2023-10-27T15:35:56.637Z
Duration: 25.933313
Channels: 1
00:00:00.080 --> 00:00:03.220
Yeah. As as much as, it's worth celebrating,
00:00:04.400 --> 00:00:05.779
the first, spacewalk,
00:00:06.319 --> 00:00:07.859
with an all female team,
00:00:08.475 --> 00:00:10.715
I think many of us are looking forward
00:00:10.715 --> 00:00:13.215
to it just being normal and
00:00:13.835 --> 00:00:16.480
I think if it signifies anything, It is
00:00:16.779 --> 00:00:18.700
to honor the the women who came before
00:00:18.700 --> 00:00:21.680
us who, were skilled and qualified,
00:00:22.300 --> 00:00:24.779
and didn't get the same opportunities that we
00:00:24.779 --> 00:00:25.439
have today.
When transcribing https://dpgr.am/spacewalk.wav, and running it through our library, this is the SRT output.
from deepgram_captions import DeepgramConverter, srt
transcription = DeepgramConverter(dg_response)
captions = srt(transcription)
print(captions)This is the result:
1
00:00:00,080 --> 00:00:03,220
Yeah. As as much as, it's worth celebrating,
2
00:00:04,400 --> 00:00:07,859
the first, spacewalk, with an all female team,
3
00:00:08,475 --> 00:00:10,715
I think many of us are looking forward
4
00:00:10,715 --> 00:00:14,235
to it just being normal and I think
5
00:00:14,235 --> 00:00:17,340
if it signifies anything, It is to honor
6
00:00:17,340 --> 00:00:19,820
the the women who came before us who,
7
00:00:20,140 --> 00:00:23,580
were skilled and qualified, and didn't get the
8
00:00:23,580 --> 00:00:25,439
same opportunities that we have today.
You can learn more about the Deepgram API at developers.deepgram.com.
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