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Descript – A collaborative audio/video editor that works like a doc

descript.com

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Re: Descript – A collaborative audio/video editor that works like a doc

#32

Post by XCSme »

The video is one of the best I've seen, really makes me excited for the product.

As for the product itself, I think the biggest "feature" is the ability to cut the audio by cutting the transcript, which makes it easier to quickly edit files. Transcribing is pretty common, the dubbing also sounds interesting but depends on how good the quality is.

I think the use-case for this is not YouTubers who expect high-quality, but social-media users who want to generate more average-quality content in a short amount of time.

Re: Descript – A collaborative audio/video editor that works like a doc

#34

Post by cush »

onion2k wrote: post #9

This looks amazing for audio. There's no doubt that this will massively improve podcasts, radio, etc. I can't imagine watching a video that's been chopped up like that would be a particularly nice experience though. Editing video to remove unwanted sections and not have it look like people's heads are jumping around weirdly is really hard. Cuts are really noticeable. If they've managed to fix that with ML it's going…

Every modern YouTube video is cut just like this. It looks good. Jumping heads turn out to not look bad, when the audio flows perfectly.

https://youtu.be/2UP6CSZsc5o

Re: Descript – A collaborative audio/video editor that works like a doc

#35

Post by cush »

tgirod wrote: post #29
onion2k wrote: post #9

This looks amazing for audio. There's no doubt that this will massively improve podcasts, radio, etc. I can't imagine watching a video that's been chopped up like that would be a particularly nice experience though. Editing video to remove unwanted sections and not have it look like people's heads are jumping around weirdly is really hard. Cuts are really noticeable. If they've managed to fix that with ML it's going…

I wonder if deep learning algorithms such as worldsheet [0] would help in simulating multiple angles, so the program can switch from one angle to another on cuts, to make them less jarring ... [0] https://worldsheet.github.io/

How is it jarring though? Most modern YouTube videos look just like this

Re: Descript – A collaborative audio/video editor that works like a doc

#37

Post by robenkleene »

iansinnott wrote: post #8

It's a very cool product, which I've only used briefly. However, product aside, their promotional videos are _phenomenal_. Not sure if they are making these in-house or some company is putting them together, but someone is doing a great job.

Both this video (https://sandwich.co/work/descript-video/), and their original promotional video (https://sandwich.co/work/its-how-you-make-a-podcast/), were done by Sandwich.

Re: Descript – A collaborative audio/video editor that works like a doc

#38

Post by dstick »

robenkleene wrote: post #37
iansinnott wrote: post #8

It's a very cool product, which I've only used briefly. However, product aside, their promotional videos are _phenomenal_. Not sure if they are making these in-house or some company is putting them together, but someone is doing a great job.

Both this video ( https://sandwich.co/work/descript-video/ ), and their original promotional video ( https://sandwich.co/work/its-how-you-make-a-podcast/ ), were done by Sandwich.

That's amazing, so fun to watch and feels 0% forced. I'm impressed.

Re: Descript – A collaborative audio/video editor that works like a doc

#39

Post by albertzeyer »

mikewarot wrote: post #13

This is amazing, I wonder how I can do this offline, using open source tools. Are there any really good open source speech to text programs? I imagine it's going to involve a pre-trained neural net. [update] Following a thread https://news.ycombinator.com/item?id=20097542 It looks like I might be able to do this (speech recognition) in less than real time (because I don't have a GPU) using https://github.com/mozilla/…

Yes, there are really good open source speech to text tools (automatic speech recognition (ASR) is the common name for that).

Kaldi (https://kaldi-asr.org/) is probably the most well known, and supports hybrid NN-HMM and lattice-free MMI models. Kaldi is used by many people both in research and in production.

Lingvo (https://github.com/tensorflow/lingvo) is the open source version of Google speech recognition toolkit, with support mostly for end-to-end models.

ESPNet (https://github.com/espnet/espnet) is good and well known for end-to-end models as well.

RASR (https://github.com/rwth-i6/rasr) + RETURNN (https://github.com/rwth-i6/returnn) are very good as well, both for end-to-end models and hybrid NN-HMM, but they are for non-commercial applications only (or you need a commercial licence) (disclaimer: I work at the university chair which develops these frameworks).

Wav2Letter (https://github.com/facebookresearch/wav2letter), the tool by Facebook.

These are probably just the most well known. There are many others as well. DeepSpeech is inferior to all the ones above, but maybe simpler.

Important is also the data to train these, but you will find quite some resources online for English, e.g. Tedlium, Librispeech, etc.

You will find lots of resources actually for ASR. Some random links:

https://github.com/gooofy/zamia-speech

https://commonvoice.mozilla.org/en/datasets

https://www.openslr.org/resources.php

To add: If you want to do sth like Descript, you are mostly also interested in accurate time-stamps of the recognized text (start and end time of each spoken word). The end-to-end models are usually not so good at this (the goals is mostly to get a good word-error-rate (WER)). The conventional hybrid NN-HMM is maybe actually a better choice for this task.

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