21–30 of 118 posts
I'd be curious about what happens when the ASR fails. This is not the place to guess or AI-hallucinate. As a pilot, I can always ask "Say Again" over the radio if I didn't understand. ASR can't do that. Also, it would be pretty annoying if my readback was correct, but the system misunderstood either the ATC clearance or my readback and said NO.
> The latest system transcribes the VHF control audio at about ~1.1% WER (Word Error Rate), down from a previous record of ~9%. I'd be curious about what happens when the ASR fails. This is not the place to guess or AI-hallucinate. As a pilot, I can always ask "Say Again" over the radio if I didn't understand. ASR can't do that. Also, it would be pretty annoying if my readback was correct, but the system misunderstoo…
In the very short term, we're deploying this tech more in a post-operation/training role. Imagine being a student pilot, getting in from your solo cross country, and pulling up the debrief will all your comms laid out and transcribed. In this setting, it's helpful for the student to have immediate feedback such as "your readback here missed this detail...", etc. Controllers also have phraseology and QA reviews every 30 days where this is helpful. This will make human pilots and controllers better.
Next, we'll step up to active advisory (mapping to low assurance levels in the certification requirements). There's always a human in the loop that can respond to rare errors and override the system with their own judgement. We're designing with observability as a first-class consideration.
Looking out 5-10 years, it's conceivable that the error rates on a lot of these systems will be super-human (non-zero, but better than a human). It's also conceivable that you could actually respond "Say Again" to a speech-to-speech model that can correct and repeat any mistakes as they're happening.
Of course, that's a long ways from now. And there will always be a human in the loop to make a final judgement as needed.
I just want to say this is such a pivotal problem to solve in this era of aviation. Looking forward to the progress you all make here. If you need any help on the product or sales side, let me know!
> The latest system transcribes the VHF control audio at about ~1.1% WER (Word Error Rate), down from a previous record of ~9%. I'd be curious about what happens when the ASR fails. This is not the place to guess or AI-hallucinate. As a pilot, I can always ask "Say Again" over the radio if I didn't understand. ASR can't do that. Also, it would be pretty annoying if my readback was correct, but the system misunderstoo…
Good and fair questions. In the very short term, we're deploying this tech more in a post-operation/training role. Imagine being a student pilot, getting in from your solo cross country, and pulling up the debrief will all your comms laid out and transcribed. In this setting, it's helpful for the student to have immediate feedback such as "your readback here missed this detail...", etc. Controllers also have phraseol…
This is effectively AGI.
And I've not seen anyone reputable suggest that our current LLM track will get us to that point. In fact there is no path to AGI. It requires another breakthrough in pure research in an environment where money is coming out of universities.
Earlier quoted context omitted.
Good and fair questions. In the very short term, we're deploying this tech more in a post-operation/training role. Imagine being a student pilot, getting in from your solo cross country, and pulling up the debrief will all your comms laid out and transcribed. In this setting, it's helpful for the student to have immediate feedback such as "your readback here missed this detail...", etc. Controllers also have phraseol…
> Looking out 5-10 years, it's conceivable that the error rates on a lot of these systems will be super-human (non-zero, but better than a human). It's also conceivable that you could actually respond "Say Again" to a speech-to-speech model that can correct and repeat any mistakes as they're happening. This is effectively AGI. And I've not seen anyone reputable suggest that our current LLM track will get us to that p…
Great use of AI models, since language is likely enough to infer the situation.
Bulk of the instrument flight training is "mindgames" anyways - you see nothing other than instruments, your "seat in the pants" is likely to cheat you..
Possibly going a step further, the state of teaching aids available to CFIs is pretty sad, with online quizzes and pre-recorded videos being the pinnacle of what I have experienced... this would be an awesome opportunity to try and build "automatic CFI" - not counting for AATD time under current rules but better than chair-flying (the process of imagining a flight and one's reactions).
> The latest system transcribes the VHF control audio at about ~1.1% WER (Word Error Rate), down from a previous record of ~9%. I'd be curious about what happens when the ASR fails. This is not the place to guess or AI-hallucinate. As a pilot, I can always ask "Say Again" over the radio if I didn't understand. ASR can't do that. Also, it would be pretty annoying if my readback was correct, but the system misunderstoo…
Good and fair questions. In the very short term, we're deploying this tech more in a post-operation/training role. Imagine being a student pilot, getting in from your solo cross country, and pulling up the debrief will all your comms laid out and transcribed. In this setting, it's helpful for the student to have immediate feedback such as "your readback here missed this detail...", etc. Controllers also have phraseol…
To me, speech to text and back seems like an incremental solution, but the holy grail would be the ability to symbolically encode the meaning of the words and translate to and from that meaning. People' phraseology varies wildly (even though it often shouldn't). For example, if I'm requesting VFR flight following, I can do it many different ways, and give the information ATC needs in any order. A system that can convert my words to "NorCal Approach Skyhawk one two three sierra papa is a Cessna one seventy two slant golf, ten north-east of Stockton, four thousand three hundred climbing six thousand five hundred requesting flight following to Palo Alto at six thousand five hundred," is nice, but wouldn't it be amazing if it could translate that audio into structured data:
{
atc: NORCAL,
requester: "N123SP",
request: "VFR",
type: CESSNA_172,
equipment: [G],
location: ,
altitude: 4300,
cruise_altitude: 6500,
destination: KPAO,
}
Earlier quoted context omitted.
Good and fair questions. In the very short term, we're deploying this tech more in a post-operation/training role. Imagine being a student pilot, getting in from your solo cross country, and pulling up the debrief will all your comms laid out and transcribed. In this setting, it's helpful for the student to have immediate feedback such as "your readback here missed this detail...", etc. Controllers also have phraseol…
Thanks for that. It must be exciting to be applying software skills to aviation. Life goals! To me, speech to text and back seems like an incremental solution, but the holy grail would be the ability to symbolically encode the meaning of the words and translate to and from that meaning. People' phraseology varies wildly (even though it often shouldn't). For example, if I'm requesting VFR flight following, I can do it…
Kidding aside, yes, you're exactly right. We're already doing this to a large degree and getting better. Lots of our own data labeling and model training to make this good.