OpenAI Whisper Speaker Diarization - Transcription with Speaker Names 

Thank you!

why its down

Mr. Patel, I can't find any online sites who do speaker diarization accurately. I don't have a GPU on my system. I am ready to pay if the speaker identification is absolutely accurate. Do you know of such services?

Any time!

Glad to be helpful

It's very useful ☺️

It sounds like an interesting project. Becoming a dev is more about trying even though you don't know what you are doing, googling stuff and going step by step on what does each line does broadly. Progress is gradual! I encourage you to try it yourself 😊

change the audio to mono

@@JoseMorenoofi Thanks, it worked

@@JoseMorenoofi Thanks

@@JoseMorenoofi Hi ! I get that assertion error @dreamypujara3384 mentionned above and I'd like to know where did you make that change from audio to mono... Thanks : )

​@@JoseMorenoofican you please explain how to do that

True. Code does not work. please fix. I need it.

same problem.

Same problem, in my case I am using spanish, looks like the problem is with tildes e.g:"ó".

I solved the problem replacing the line f = open("transcript.txt", "w") by the following f = open("transcript.txt", "w", encoding="utf-8")

@@humbertucho2724 that worked for me, thanks.

@@humbertucho2724 Thanks mate!

Having this same issue - wondering if its a more widespread issue or specific to this configuration of pyannote. Thinking about trying NeMo if this poses a problem

you just have to add [if waveform.shape[0] > 1: waveform = waveform.mean(axis=0, keepdims=True)] right before the return of [segment_embedding()]

You're welcome

same error here: --------------------------------------------------------------------------- AssertionError Traceback (most recent call last) in () 1 embeddings = np.zeros(shape=(len(segments), 192)) 2 for i, segment in enumerate(segments): ----> 3 embeddings[i] = segment_embedding(segment) 4 5 embeddings = np.nan_to_num(embeddings) 1 frames /usr/local/lib/python3.9/dist-packages/pyannote/audio/pipelines/speaker_verification.py in __call__(self, waveforms, masks) 316 317 batch_size, num_channels, num_samples = waveforms.shape --> 318 assert num_channels == 1 319 320 waveforms = waveforms.squeeze(dim=1) AssertionError: And yes :-) I am na totally new coder

The same thing happened to me.

same, I noted it gives such an error with more or less big audio files. smaller ones worked fine. not sure if it's the reason though.

Guess I found the answer! If you convert the initial audio file from stereo to mono it works fine

@@Hiroyuki255 how do you do it?

You can run this locally, but you need a decent GPU to do it. Just make a python script out of the colab

it does not work anymore

If you have enough GPU power locally, YES. I also assume you have Python and all the required libraries installed.

I'm using it from the model (not the API)

@@1littlecoder the whister model then is not the one on openai st. In my case I am looking for a method based on openai, the reason is to be able to ensure the privacy of the information since I want to do it with company data, do you know if it is possible?

@@JorgeLopez-gw9xc Hi Jorge, I am having the same question as yours, I would be really appreciative if you have figured out the solution and happy to share some ideas with me

I'm not sure if it'd work fine then. I have not checked it.

you need to store person's voice embeddings and then compare (some similarity) and map with the one in the samples generated

Export into text then do a search and replace.