Existing (and affordable) offerings are so good that they can cope with shitty recordings off a phone speaker and maintain ~97% accuracy over hour-long conversations. I'm sure it's been an absolute godsend for law enforcement other people who need to gather poor-quality audio at scale, though much less great for the targets of repressive authority.
Having this fully open is a big deal though - now that level of transcription ability can be wrapped as an audio plugin and just used wherever. Given the parallel advances in resynthesis and understanding idiomatic speech, in a year or two I probably won't need to cut out all those uuh like um y'know by hand ever again, and every recording can be given an noise reduction bath and come out sounding like it was recorded in a room full of soft furniture.
97% accuracy means roughly three or four errors per minute of speech. That seems potentially extremely problematic for something like law enforcement use where decisions with significant impact on people's day and/or life might be made on the basis of "evidence".
Would you want to review this fully before going into court, absolutely - because you'd want to play the recording to a jury for emotional impact. Can you rely on it when you want to quickly read through hours of conversation and make decisions about whether to invest further resources (which might just mean another hour of listening back to the original audio)? Also absolutely. Bear in mind that a lot of these errors have little to no semantic impact, being on the same level as typos or misspellings in a written communication.
Bear in mind too that if law enforcement (honest or not) is so interested in you that they're willing to record your conversations, your day is already ruined, you just don't know it yet. The change here is one of scale rather than quality.
(edit for clarification: errors are not always something like "[UNINTELLIGIBLE]", where the system knows it doesn't know; they can also be misrecognitions that the system believes in with high confidence.)
Look, I have decades of experience dealing with human speech, and not just as an editor - I can trace the human voice from neural impulses in Broca's region through the physiology of vocal production, mechanical transduction into electrical signals, discrete fourier transforms of the resultant waveforms into spectral information and back again, the reproduction of altered signals from time-aligned speakers to create a sense of spatialization, how those are processed in the human ear, and how the cilia are connected by nerves back to your brain. I'm a good enough editor that I can recognize many short words by sight of a waveform, or make 10 edits in a row by sight and know it will sound good on playback.
So when I say that machine transcription is as good as human realtime transcription now, I say so with the clear expectation that those decades of craft are very close to being rendered obsolete. I absolutely expect to hand off the mechanical part of editing to a machine within 2 years or so. It's already at the stage where I edit some interviews as text, like in a word processor, and then export the edited document as audio and it's Good Enough - not for every speaker, but more than half the time.
NPR and a lot of commercial broadcasters cut their material this way already, because you can get the same result from 30 minutes of reading and text editing that would require 3 hours of pure audio editing with no transcription.
Alignment of video to text is a big problem for me too.
You can even add/modify words that weren't originally there https://www.descript.com/overdub
Would you go as far as to assert machine transcription can be used as an objective benchmark of a speaker’s verbal legibility?
It is fraught with political and interpersonal dynamics to approach someone even privately one on one today and gently suggest their career would get a huge boost if they hired a voice coach to help improve their verbal communication delivery. So even when I don’t directly mention their accent, it becomes a very sensitive subject with many.
However, if audio professionals like you can point to a system and say the raw biomechanics and acoustic physics of the world dictate that this is as physically and psychometrically good as audio parsing of human speech gets regardless whether the system was biologically evolved or ML evolved, the conversation can be couched even more objectively.
I enable recording and voice transcription in every meeting I can (ostensibly for DE&I but really for my own selfish purposes), and already observe in myself I have to work hard to overcome a tendency to gloss over speakers who don’t transcribe well when I review meeting transcripts to jot down any key information I might have missed taking notes upon during the meeting.
Note that I’m perfectly aware that my foreign language verbal skills are nowhere near the English skills of those I have tried to help. If the lingua franca of the coding world switched to Urdu tomorrow, then I’d hire help to learn and polish my spoken Urdu, like I went to a speech coach when learning public speaking because I can always use help in the many skills I lack.
Suppose 90% of the errors are in the 10% where the model is least confident. Then you can review just 10% of your content and take a 2% error rate down to 0.2% error rate.
The principle is that the engines have different failure modes (hopefully) and therefore the 2-3% error rate of each engine is in different areas of the audio. The key underlying assumption is that the events are mutually exclusive.
With 3 engines, you can use something like 2-of-3 stream matches to override the stream that mismatches.
Not having to pause + rewind will save a ton of time for that 3%.
“During his term as President of the United States, Donald Trump made tens of thousands of false or misleading claims. The Washington Post's fact-checker had tallied the number as 30,573 by January 2021, an average of about 21 per day by the end of his presidency.” [1][2][3][4]
I think it’s fair to say there would be a 100 hour long plus video / documentary if they were all compiled into one. lovely!
- [1] Fact Checker (January 20, 2021). "In four years, President Trump made 30,573 false or misleading claims". The Washington Post. Archived from the original on January 20, 2021.
- [2] Kessler, Glenn (January 23, 2021). "Trump made 30,573 false or misleading claims as president. Nearly half came in his final year". The Washington Post. Archived from the original on January 24, 2021. Retrieved January 24, 2021.
- [3] Elfrink, Tim (August 14, 2020). "'Do you regret at all, all the lying you've done?': A reporter's blunt question to Trump goes unanswered". The Washington Post. Retrieved August 14, 2020.
ML systems somewhat notoriously do not necessarily make the same sorts of errors that a human would. And I'd expect a large portion of the errors to be transcribing the wrong words rather that indicating that a word couldn't be transcribed. That sort of error means that you can't really get away with manually reviewing just 3% of the audio.
And there are humans in the loop too, and an enormous amount of redundancy in the questions and answer, so even plausible false transcriptions will get picked up on if they matter. Nobody gets sent to jail simply because the transcription process - human or machine - accidentally substitutes "I did it" in place of "I didn't" midway through a two hour interview.
For entertainment purposes AI transcription is awesome.
For serious business applications the ability to recognize mistakes will continue to be a field to which serious attention is given. It would be interesting to see AI processes double check itself, and also run a logic check on whether the transcription makes sense. So that it can report sections flagged as incongruous or of dubious reliability.
Humans, however, are not simply metric optimizers. Though it's always in the interest of those corporations producing metric optimizers (i.e. models) to paint humans as such, so their models shine in comparison. They want humans to look like bad machines, so it looks like they should be automated. Not to say they shouldn't in many cases, just that there's a clear one-sidedness in all corporate PR (and funded research, especially that research which is also PR).
All this to say that yes I agree with you. And if we humans don't want our unsustainable economic growth to turn us even more into machines (as our bureaucratic creep has done quite well thus far), we should fight such rhetoric that aims to paint humans simply as machines or task-doers.
1. Set up a computer with voice recognition software that flags certain patterns.
2. Connect computer to voice call communication network.
3. Configure computer to switch between calls every x number of seconds.
Think of it like a system to generate leads for law enforcement that can be integrated with other systems to produce the best quality leads.
>The right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures, shall not be violated, and no Warrants shall issue, but upon probable cause, supported by Oath or affirmation, and particularly describing the place to be searched, and the persons or things to be seized.
Besides I wasn't talking about the USA when I said this. I was remembering a conversation I once had with a person who worked as a technician in a telephone exchange.
Power always just finds a way to rationalize what it wants to do.
For technical content, I use Rev.com and provide a glossary and real humans do the transcript. Other AI transcription services get lots wrong because the context often matters. Words like "TCP/IP" or "FAT disk format" or "Big Endian" I've never found AI so far to handle well.
I'm interested to test out whisper on this one.
Although I don't know if they're using anything similar to what you suggest. Very cool idea, anyway!
I will try to put the code to the test, see how it goes.
> Nous établissons que l'utilisation de données d'un tel nombre et d'une telle diversité est la raison pour laquelle le système est à même de comprendre de nombreux accents...
It doesn't sound natural at all. An idiomatic formulation would be more along the lines of:
Le recours à un corpus [de données] si riche et varié est ce qui permet au système de comprendre de nombreux accents (With 'corpus', 'données' is implied.)
Of course this is just an example, and I'm sure other French speakers could come up with a different wording, but "données d'un tel nombre et d'une telle diversité" sounds really wrong.
This is also weird and convoluted:
> Nous distribuons en tant que logiciel libre le code source pour nos modèles et pour l'inférence, afin que ceux-ci puissent servir comme un point de départ pour construire des applications utiles
It should at least be "le code source DE nos modèles" and "servir DE point de départ", and "en tant que logiciel libre" should placed at the end of the proposition (after 'inférence').
Also, "construire" isn't used for code but for buildings, and "applications utiles" is unusual, because "utiles" (useful) is assumed. "...pour le développement de nouvelles applications" would sound more French.
I kind of doubt it though -- the speaker doesn't have a Canadian accent (which is hard to miss), and in my (admittedly limited) experience, French Canadian isn't that different from French.
No one says "Nous", there, ever. Perhaps the politicians, while giving a speech. Everyone else uses the more informal "On".
I felt duped by my French classes.
It is often used for larger groups or when the group is not very personally connected. For instance when talking about your company doing something you will often use "nous". I would also use "nous" to refer to the whole list of invitees to a wedding. And in formal contextes like research papers, reports etc. You would never use "on", always "nous".
> We distribute as a free software the source code for our models and for the inference [...]
Should be
> We are open-sourcing models and inference code [...]
Another example
> We establish that the use of such a number of data is such a diversity and the reason why our system is able [...]
Should be
> We show that the use of such a large and diverse dataset leads to improved robustness [...]
Original:
Trois mille six cents fois par heure, la Seconde
Chuchote Souviens-toi !– Rapide, avec sa voix
D'insecte, Maintenant dit Je suis Autrefois,
Et j'ai pompé ta vie avec ma trompe immonde !
Remember ! Souviens-toi ! prodigue ! Esto memor !
(Mon gosier de métal parle toutes les langues )
Les minutes, mortel folâtre, sont des gangues
Qu'il ne faut pas lâcher sans en extraire l'or !
> Trois mille six cents fois par heure, la seconde chuchote « Souviens toi », rapide, avec sa voix d''insecte, maintenant dit « Je suis autrefois », et j''ai pompé ta vie avec ma trompe immonde. « Remember, souviens toi, prodigue, est au mémoire, mon gosier de métal, parle toutes les langues, les minutes, mortelles folâtres, sont des gangs qu''il ne faut pas lâcher sans en extraire l''or. »
Not bad! Far from perfect but it's a difficult text. Interesting that it works better with Baudelaire than Pascal.
Original:
> Mes révérends pères, mes lettres n’avaient pas accoutumé de se suivre de si près, ni d’être si étendues. Le peu de temps que j’ai eu a été cause de l’un et de l’autre. Je n’ai fait celle-ci plus longue que parce que je n’ai pas eu le loisir de la faire plus courte. La raison qui m’a obligé de me hâter vous est mieux connue qu’à moi. Vos réponses vous réussissaient mal. Vous avez bien fait de changer de méthode ; mais je ne sais si vous avez bien choisi, et si le monde ne dira pas que vous avez eu peur des bénédictins.
Transcription:
> Mes rêves errent pères, mais l'detre navais pas accoutumé de se suivre de si près ni d'detre si étendu. Le peu de temps que j'sais eu a été cause de l'de l'de l'de autre. J'sais n'detre plus longue que parce que j'sais pas eu le loisir de la faire plus courte. La raison qui m'sa obligée de me hâter vous est mieux connue qu'moi. Vos réponses vous réussissaient mal. Vous avez bien fait de changer de méthode, mais je ne sais pas si vous avez bien choisi et si le monde ne dira pas que vous avez eu peur des bénédictes.
Here there are many more mistakes, so many that the beginning of the text is unintelligible. The language from the 17th century is probably too different. Still on the "medium" model, as the large one crashes the Colab (not sure how to select a beefier machine.)
Still fascinating and exciting though.
My test gives that, much better than yours:
Mes *rêverants* pères, mes lettres n'avaient pas accoutumé de se suivre de si près ni d'être si étendues. Le peu de temps que j'ai eu a été cause de l'un et de l'autre. Je n'ai fait celle aussi plus longue que parce que je n'ai pas eu le loisir de *l'af*faire plus courte. La raison qui m'a obligé de me *ra*ter vous est mieux connue qu'à moi. Vos réponses vous réussiss*ez* mal. Vous avez bien fait de changer de méthode. Mais je ne sais si vous avez bien choisi et si le monde ne dira pas que vous avez eu peur des bénédict*eurs*.
I tried the beginning of L'étranger (because you seem to be a fan of Camus ;-)
Here's the original:
> Aujourd’hui, maman est morte. Ou peut-être hier, je ne sais pas. J’ai reçu un télégramme de l’asile : « Mère décédée. Enterrement demain. Sentiments distingués. » Cela ne veut rien dire. C’était peut-être hier.
> L’asile de vieillards est à Marengo, à quatre-vingts kilomètres d’Alger. Je prendrai l’autobus à deux heures et j’arriverai dans l’après-midi. Ainsi, je pourrai veiller et je rentrerai demain soir. J’ai demandé deux jours de congé à mon patron et il ne pouvait pas me les refuser avec une excuse pareille. Mais il n’avait pas l’air content. Je lui ai même dit : « Ce n’est pas de ma faute. » Il n’a pas répondu. J’ai pensé alors que je n’aurais pas dû lui dire cela. En somme, je n’avais pas à m’excuser. C’était plutôt à lui de me présenter ses condoléances.
Here's the transcription:
> Aujourdhui, maman est morte, peut être hier, je ne sais pas. J''ai reçu un télégramme de l''asile. Mère décédée, enterrement demain, sentiment distingué. Cela ne veut rien dire. C''était peut être hier.
> L''asile de Vieillard est à Maringot, à 80 km d''Alger. Je prendrai l''autobus à deux heures et j''arriverai dans l''après midi. Ainsi, je pourrai veiller et je rentrerai demain soir. J''ai demandé deux jours de congé à mon patron et il ne pouvait pas me les refuser avec une excuse pareille. Mais il n''avait pas l''air content. Je lui ai même dit, ce n''est pas de ma faute. Il n''a pas répondu. J''ai alors pensé que je n''aurais pas dû lui dire cela. En somme, je n''avais pas à m''excuser. C''était plutôt à lui de me présenter ses condoléances.
Except for the weird double quotes instead of the single apostrophe ('), it's close to perfect, and it only uses the "medium" model.
This is extremely exciting and fun! Happy to try other texts if you have something specific in mind!
That said there is value in integration of this into other things.
Perhaps it will encourage people to add voice command to their apps, which can be sent to gpt3
https://www.reddit.com/r/IsItBullshit/comments/2rztov/isitbu...
But it'd be really easy to prove if it were true and noone has offered proof. And there've been plenty of people who've looked for such proof, afaict.
My default assumption in such cases is that it is likely false.
There are at least two companies that have branded [..] Kosher Gelatin™. One of them makes gelatin that is considered non-kosher by all of the major kashrus agencies.
"Kosher Gelatin®", when in the ingredients, just means the product contains pork.
I remember thinking that surely an image of a hamburger does not legally constitute a zero.
The 4 examples are stunningly good (the examples have speakers with heavy accents, speaking in foreign language, speaking with dynamic background noise, etc.), this is far and away better than anything else I've seen. Will be super curious to see other folks trying it out and seeing if it's as robust as it seems, including when confronted with audio speech with natural tics and uhhh's and uhmm's and everything in-between.
I think it's fair to say that AI-transcription accuracy is now decidedly superior to the average human's, what the implications of this are I'm not sure.