Sound like a bad patch for hallucinations.

And there are legitimate cases where repitition can happen.

Ignoring repeated prompts does not stop the output of repeated text, the model can still produce repeated text. I think this patch is a method to improve the model's robustness, similar to --temperature_increment_on_fallback. This patch reduces the possibility of falling into endless loops due to repeated text. As mentioned above, I am using Whisper to process songs and conferences recording, and I have observed that after applying this change, there are hardly any cases where the entire transcription is ruined due to repeated hallucinations (if any, re-running it once can solve the problem).

I understand that this change may affect some repeated sentences, but it's still better than --condition_on_previous_text False or ruining the entire transcription.

And there are legitimate cases where repitition can happen.

Of course song lyrics are a legitimate case where repetition happens. But looking at the PR it looks to only remove repeated text from the prompt, not from the output, so the model is still allowed to output repetition if there really is repetition in the audio, but it is not influenced more so in that direction by having repetition in the prompt.

I understand that this change may affect some repeated sentences

Do you have an example?

Do you have an example?

Yes, I have noticed one example. https://www.youtube.com/watch?v=a6lvjW8xunc

whisper --model large --language Japanese --task transribe audio.webm

The correct output is

[01:12.000 --> 01:15.000] Always I miss you
[01:16.000 --> 01:18.000] Miss you         
[01:19.000 --> 01:20.000] Miss you                                                                                                                                                                                                             
[01:21.000 --> 01:22.000] Oh miss you
......
[01:34.000 --> 01:36.000] Always I miss you
[01:37.000 --> 01:38.000] Miss you
[01:38.000 --> 01:40.000] Miss you
[01:41.000 --> 01:43.000] Oh miss you
[01:44.000 --> 01:46.000] Miss you
......
[03:13.000 --> 03:15.000] Always I miss you
[03:16.000 --> 03:18.000] Miss you
[03:19.000 --> 03:20.000] Miss you
[03:21.000 --> 03:22.000] Oh miss you
......
[03:33.000 --> 03:35.000] Always I miss you
[03:36.000 --> 03:38.000] Miss you
[03:39.000 --> 03:40.000] Miss you
[03:41.000 --> 03:42.000] Oh miss you
......
[03:54.000 --> 03:56.000] Always I miss you
[03:56.000 --> 03:59.000] Always I miss you
[04:07.000 --> 04:09.000] Miss you

However, after this patch, the [01:38.000 --> 01:40.000] Miss you is missing

[01:12.000 --> 01:15.000] Always I miss you
[01:16.000 --> 01:18.000] Miss you
[01:19.000 --> 01:20.000] Miss you
[01:21.000 --> 01:22.000] Oh miss you
......
[01:34.000 --> 01:36.000] Always I miss you
[01:37.000 --> 01:41.000] Miss you
[01:41.000 --> 01:44.000] Oh miss you
[01:44.000 --> 01:46.000] Miss you
......
[03:13.000 --> 03:15.000] Always I miss you
[03:16.000 --> 03:18.000] Miss you
[03:19.000 --> 03:20.000] Miss you
[03:21.000 --> 03:22.000] Oh miss you
......
[03:33.000 --> 03:35.000] Always I miss you
[03:36.000 --> 03:38.000] Miss you
[03:39.000 --> 03:40.000] Miss you
[03:41.000 --> 03:42.000] Oh miss you
......
[03:54.000 --> 03:56.000] Always I miss you
[03:56.000 --> 03:59.000] Always I miss you
[04:07.000 --> 04:09.000] Miss you

Inaccurate end timestamps cause the next window to start too late and miss what was spoken, and this can often be fixed by enabling word_timestamps which produces more accurate timestamps.

Since your timestamps look like they're all integers, it suggests you don't have word_timestamps enabled. If that's the case, does it improve with word_timestamps?

May I ask if there is an official solution to the problem of repeated hallucinations? This problem is very serious.