I am using Whisper API to transcribe some video lectures and conferences. It is actually working very well, even for smaller languages it is on much better level than I have seen before. I have two questions though: 1.) Is it possible to get timecodes via API? I can’t see it in the docs, so I am g…

Sorry, this isn’t really an answer, but I did spend a bit of time looking into 1 and I also couldn’t find any way to add timecodes. The locally hosted version returns several pieces with just the text being one and the timecodes beign another, and it looks like the api just returns the text portion. …

I guess we will have to wait or to use the self-hosted version. I am now looking into some possibilities of recognizing speakers, but it seems I would need to a) do that in Python first, via some library, b) send separate audio files on basis of that to the transcription. Not sure if there is more …

You can define the format you want to have returned as body form field. If you define it as “srt”, you get back the timestamps as well e.g. via curl you add the following parameter --form response_format=srt

Revised (see below for how to get timecode from the api), the advantage of using the API over self hosting is performance and model size, if you wish to run a very capable model from a low power device, offloading that computational task to a remote, enterprise class compute facility is an attractiv…

add form field, response_format=x where x is srt or verbose_json IDK You can also try deepgram, they offer whisper models at a cheaper price and they have diarization+timecodes

[image] Whisper, how to tag different people in (sound) conversation API Here is a video I ran across awhile ago, where they use Whisper (open source version) for the transcription, and AWS Transcribe to detect the speakers. Note: Also a GitHub link to code in …

whisper api has timestamp like what the previous posters mentioned. just set the “response_format” parameter to srt or vtt. if you are using the OpenAI Node.JS library: const resp = await openai.createTranscription( fs.createReadStream("audio.mp3"), // file "whisper-1", // m…

Here’s the Python version to specify response format: import openai audio_file = open("/path/to/file.mp3", "rb") transcript = openai.Audio.transcribe( "whisper-1", audio_file, response_format="vtt" )

I’ve got it, thanks everyone. I think this could be used for speaker recognition as well. a) Get timecodes b) Paralelly to sending audio to transcription, do a speaker recognition with other tools. c) Compare transcription timecodes and timecodes for speaker recognition. d) Insert information in…

Whisper API: a) Timecodes; b) how good is open-source vs API?

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jtapiovaara June 8, 2023, 12:12pm 7

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Whisper API: a) Timecodes; b) how good is open-source vs API?

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