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update transcribe docs to new version
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mkdocs/docs/HPC/transcribe.md

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@@ -12,15 +12,16 @@ The supported flow is:
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- Upload audio or video file using the `Files` interface of the web portal
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- Configure transcription via the `Interactive Apps` -> `Transcribe` application (currently under `Testing` section at the bottom);
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you can select `Whisper inputfile`.
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you can select `Whisper inputfile` and `Whisper language`.
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- Launch it and wait. Connecting to the running transcription is entirely optional; there is nothing interactive to do.
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You will also receive an email when the transcritpion started.
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- Upon completion, you will receive an email with link to the result directory. This info will also be shown in the application session under
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`My interactive sessions` (but the session data is only available for a week).
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The result directory has a subdirectory per language with the text files and some metadata in JSON format of the transcritpion itself and input file.
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The result directory has a subdirectory per language (transcription and optional translation)
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with the text files and some metadata in JSON format of the transcritpion itself and input file.
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This is intentionally kept simple. There is also no risk of loosing previous results
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## Performance and default settings
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The defaults should give the best balance between quality, performance and time to result.
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You can expect approx 10 minutes of transcription time per language and per hour of input using the default flavour.
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This combined with an almost immediate start time is the best combination for the intended use case.
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You can expect approximate 10 minutes of transcription time per hour of input and
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approximate 1 minute per translation language using the default flavour.
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This performance combined with an almost immediate start time is the best combination for the intended use case.
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There should be enough resources available to get this result most of the time.
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## Advanced options
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### Whisper language
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Using the `Automatic detection` (the default), whisper determines the spoken language based on the first 30 seconds of audio.
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If, for some reason, the autodection fails (e.g. the input file starts with silence or some music), you can force one of the languages.
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When selecting more than one, the transcription will be done separately for each language
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(this will also increase your total running time, so you might also want to increase the `Time`).
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The selected language will also determine the output language. However, this is ***not*** meant as a translation feature;
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although the quality is not that bad if your languages have enough similarity.
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### Cluster
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### Translation target languages
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Changing the cluster from the interactive cluster will give you access to much better GPU,
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but at a penalty of having to wait in the queue of the other cluster typically for a much longer time
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than it will take to complete the transcription on the default cluster.
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Select one or more languages to translate to. Hold the `Ctrl` button pressed while clicking to select (or unselect) languages.
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## Resources
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The translation is run after the transcription, and is separate from the Whisper based process.
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If you select a language to translate to that is also the `Whisper language`, there will be no translation generated for it.
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Default settings of 4 cores with at least 10GB of RAM and 1 hour (wall)time should be enough for most transcriptions.
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The default languages are `Dutch` and `English`. If e.g. you have a Dutch spoken video (and select Dutch as the `Whisper language`),
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the end result will be a Dutch transcription and an English translation of the Dutch transcription. (And thus no `Dutch-to-Dutch` translation.)
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There is thus no need to unselect the languages each time based on changing input languages.
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### Model
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Default model is `large-v3`, others can be choosen but should be careful to compare resulting speed and/or quality differences.
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### Flavour
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We currently support 2 flavours: `whisper` (the OpenAI reference implementation), and `whisper-ctranslate2`
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(a faster version with some extras). Benchmarks indicate that `whisper-ctranslate2` is about 4 times faster than `whisper`,
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but might have some lower quality.
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### Model
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Default model is `large-v3`, others can be choosen but should be careful to compare resulting speed and/or quality differences.
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### Task
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From the selected (or auto-detected) source speech language, you can choose to transcribe to the same language or to `English`.
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You can use this last option to translate to English (as opposed to force the detection of the source language as if it was spoken in English).
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### Cluster
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Changing the cluster from the interactive cluster will give you access to much better GPU,
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but at a penalty of having to wait in the queue of the other cluster typically for a much longer time
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than it will take to complete the transcription on the default cluster.
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## Resources
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Default settings of 4 cores with at least 10GB of RAM and 1 hour (wall)time should be enough for most transcriptions.

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