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I have some skepticism. Humans can’t process multiple audio streams simultaneously. Recognizing faces is a poor analogue to compare with, it would be more simil
by mlthoughts2018 6y ago
I have some skepticism. Humans can’t process multiple audio streams simultaneously. Recognizing faces is a poor analogue to compare with, it would be more similar to photostitching several faces all superimposed on top of each other and asking a human to identify each component face, which humans are also terrible at.
But we also rarely need realtime solutions for this. Casually tracking gross features from a mixed audio source, like a big crowd, is easy, but we almost never need to be actively listening and disambiguating between several deliberate audio signals all at once. Human communication just isn’t setup that way, though I’m sure there are niche exceptions.
Note here that video conferencing is emphatically not an example of an exception. You still need to have synchronous order of speaking, not because technology lacks the ability to separate the streams for the listener, but because the listener cannot pay attention to more than one stream at a time.
To me this technology seems almost exclusively useful for surveillance and offline audio analysis or audio synthesis / mixing.
Still possibly valuable, but definitely not in any fundamental way that would significantly change or augment realtime verbal communication.
- newsbinator 6y agoWe are much better at faces than we are at voices: • Imagine I show you 10 photos of faces. Then I come back 15 minutes later and ask you to pick them out from a set of 20 faces. • Imagine I play you 10 audio snippets of someone talking. Then I come back 15 minutes later and ask you to pick them out from a set of 20 audio snippets of people talking. That said, I agree with you that primarily this technology would be useful for surveillance. If you can zoom in on any given conversation happening at New York Penn Station, you're basically in the Bourne Identity, with all the privacy-destroying overreach that entails.
- mlthoughts2018 6y agoI think you completely missed the point. If you think the overall fact that humans are better at face identification than audio identification is relevant here, you missed the point, since that high level fact is not related to this specific problem or the comparison being made.
- sillysaurusx 6y agoCan you explain the point? Because I've missed it too.
- mlthoughts2018 6y agoThe task of disambiguating speakers, relative to skill at other audio processing tasks, is more similar to disambiguating superimposed faces, relative to skill at other vision tasks. It is not similar to quickly recognizing several different faces that are present in a video stream. Tasks requiring simultaneous processing of focused attention on multiple input streams are not very related to human visual or audio processing. These types of tasks are not similar to attending to things in peripheral vision or peripheral audio.
- sillysaurusx 6y agoI'd fail task #1 but excel at task #2. I have audio playing in my head constantly. It's how I learn about the world. It also seems to be inverted from when I was younger; visuals were much more vivid then.
- dillonmckay 6y agoSame, I can often identify actors on tv shows or movies by their voice, some of which is 20 to 30 years older or later than when I originally heard the voice.
- def8cefe 6y ago> Humans can’t process multiple audio streams simultaneously. I'm not sure this is true. I think our comprehension drops when we do, but we regularly process background noise and speech at the same time, same for people interjecting over others with simple things like 'excuse me' or similar. I may be misunderstanding or stretching your point but it's interesting to think about. I also immediately jumped to surveillance tech when I read it though I can think of other areas it would be useful. Home assistants like they mention in the article would be a great use case, not for multiple inputs at the same time, but to isolate the speaker addressing the home assistant.
- wenc 6y agoI think you're right -- we mostly only talk to 1 person at a time. Where it might be useful is automated live captioning (already a feature in Microsoft Teams), especially in cultures that favor a "high involvement" conversation style where people interrupt and talk over each other (vs a "high consideration" style where everyone waits their turn). This tech might help improve transcript quality. In the article, under the subheading Why It Matters, the authors say this: [Quote] The ability to separate a single voice from conversations across many people can improve and enhance communication across a wide range of applications that we use in our daily lives, like voice messaging, assistants, and video tools, as well as AR/VR innovations. It can also improve audio quality for people with hearing aids, so it’s easier to hear others clearly in crowded and noisy environments such as parties, restaurants, or large video calls. Beyond its separating different voices, our novel system can also be applied to separate other types of speech signals from a mixture of sounds such as background noise. Our work can also be applied to music recordings, improving our previous work on separating different musical instruments from a single audio file. As a next step, we’ll work on improving the generative properties of the model until it achieves high performance in real-world conditions.
- pessimizer 6y ago> Humans can’t process multiple audio streams simultaneously. Yes they can, they can process two, and no more than two. Being able to listen to a conversation where multiple people are talking at the same time isn't processing different audio streams. It's assigning a set of sounds heard over time by timbre, subject (meaning) or relative volume to subsets representing different theoretical sources. People have very little problem doing this with a small number of potential sources (probably another seven plus or minus two thing.) Even in large crowds, we can often pick out a few individual voices of interest (if distinctive enough in timbre, position and movement (judged by volume and pitch changes), or accent/wording/subject, and follow those voices while disregarding the rest of them. edit: we might suck at multitasking, but that's not a problem a computer would have. I can't follow multiple speakers at once if they're not interacting with each other, and they're speaking quickly and overlapping, but that's a problem with context switching. With a computer I can just route the separated voices to systems that will handle them. Everybody gets their own waiter.
- ksaj 6y agoModern hearing aids do various things in attempt to separate voices in order to present them more cleanly in the 3D spacial field. It's usually referred to as voice tracking, but different companies have different buzzwords. This does very much make it easier for people with hearing aids in both ears to locate a specific voice, and focus on it at the exclusion of others, pretty much as your ears already do. They just make the stereo division more clear. So I think this newer technology is taking what already exists, to the next level. Some settings can also lower the volume of voices you aren't looking straight at. It's really quite useful if you are in a conference and everyone keeps shuffling around and trying to talk over the person who is supposed to be speaking, for example. The weird side effect is something I jokingly call "spy mode" which allows me to intensify voices behind me instead of ahead of me. Apparently it's more to benefit drivers, but it's cool hearing clearly everything going on behind you, too. Interestingly I can't use the on-board controls or even the remote to enable the "spy mode," but I can when I am connected (via bluetooth) to my cell phone and control them with the app.