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  • [whale bellows]

  • [whale whistles]

  • [whale chirps]

  • [whale bellows]

  • [whale whistles]

  • Clark: Everything in the ocean is producing some form of sound.

  • I'm Christopher Clark,

  • I'm a bioacoustic scientist,

  • and I listen to the songs of life

  • around this planet.

  • [whale bellows]

  • Clark: You listen to this expanse of the sound in the ocean.

  • It just becomes a magnificent symphony of voices,

  • and you know what?

  • Most of the voices that we're listening to today

  • we do not know who's making those sounds.

  • [curious music]

  • Allen: My name's Ann Allen.

  • I'm a research oceanographer

  • for NOAA Fisheries.

  • We use acoustics or sound in order to help us monitor

  • the whales and dolphins in the Pacific Islands.

  • [curious music continues]

  • [whale bellows]

  • [whale cries]

  • Allen: Pretty early on, I realized

  • that a lot of the methods that have been developed so far

  • were not going to work for our data.

  • Somebody would literally sit here and scan through a few hours at a time

  • marking each of these start and ends of the humpback song.

  • [whale bellows]

  • [whale chirps]

  • Harvey: Hi, my name's Matt Harvey,

  • I'm a software engineer at Google,

  • and I work on machine learning models for audio analysis

  • applied to bio acoustics.

  • Allen: Some species like fin whales make very simple sounds,

  • and our detectors are actually pretty good at those,

  • but then species like humpback whales make very complex sound types

  • that are changing all the time,

  • so having a detector that works for those sounds

  • is very, very difficult.

  • [whale cries softly]

  • [whale groans]

  • Allen: The idea with machine learning is, you train a machine learning model,

  • which is actually teaching a computer to recognize sounds

  • rather than teaching it a step-by-step process.

  • And this is humpback whale. This is humpback whale.

  • This is not humpback whale. Ignore this.

  • Harvey: We learned to predict the presence of humpback whale

  • with very high accuracy.

  • Allen: So it's doing what it's supposed to do.

  • It's doing what it's supposed to do, yeah.

  • Allen: Whoo!

  • There's not a lot known about our whale populations out here,

  • so there's so much that we could figure out

  • just from knowing who's where and when.

  • [whale bellows]

  • Allen: We've collected all this data.

  • We don't want to just hoard it.

  • We want to put it out there so that other people can use it and look at it.

  • Jongejan: When I heard the first audios of underwater recording,

  • I was amazed by that world that we typically don't hear

  • and I want to share that with more people.

  • Hi, my name is Jonas,

  • and I'm a creative technologist at Google.

  • [gentle music]

  • Jongejan: So the data you see is all visualized here as a spectrogram.

  • When you zoom all the way in, you would see a few minutes of audio,

  • and you can see the patterns of the different whale calls.

  • As you zoom out, you would be able to see several months of audio

  • at the same time on the screen.

  • And at the bottom, you see a long bar that is a heat map,

  • so using the AI to guide you where to look for whales.

  • Clark: It's absolutely critical that we learn to share.

  • What you're doing is, you're actually allowing a vista

  • into a world that's been totally hidden from us.

  • [whale bellows]

  • [whale shrieks]

  • [whale groans]

  • [whale chatters]

  • Allen: There's sounds in data sets that we don't know what they are.

  • Jongejan: We've seen that releasing a large data set

  • just creates opportunities that we have never thought about.

  • People might take this project

  • and make discoveries

  • that no one else has done before.

  • [whale squeaking]

  • Clark: You're opening up the opportunity to explore it to everybody.

  • Now you're not going to have 10 people or even 100 people.

  • You're going to have 10 million people.

  • [gentle music]

  • Clark: That's the scale we need to understand life in the ocean.

  • [whale chirps]

  • [whale bellows faintly]

  • [whale chirps]

  • [whale squeaking]

[whale bellows]

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鯨歌與人工智能,供大家探討。 (Whale Songs and AI, for everyone to explore)

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    林宜悉 發佈於 2021 年 01 月 14 日
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