Humans are far from the only species with a gift for gab, and our furry, feathered, and finned friends could have a lot to tell us. Decoding how animals communicate with one another could offer a window into the inner lives of other species and help humans realize that “animals are sentient creatures who think, who have hopes and dreams of their own,” says Con Slobodchikoff, the founder of Zoolingua, a company working on dog-to-human speech.
Teasing all this out is complex. To decipher howls, squeaks, and clicks, researchers must match the creatures making sounds with what’s happening around them. Prairie dogs, for example, utter a different series of yips when a coyote approaches than when a hawk is nearby. It’s painstaking work, especially for difficult-to-observe species like deep-diving whales or subterranean mole rats. Many animals also communicate through visual cues, touch, pheromones, or a combination of signals, some of which may be hard for us to perceive. Without a multispecies Rosetta stone, it’s hard to know if translations are accurate.
Over the past 50 years, a growing arsenal of devices has made it easier to observe these sophisticated ways animals communicate. Hydrophones on the ocean floor capture humpback whale song, and tiny wearable “biologgers” can record a bat’s every squeak. In the last decade, advances in AI have leveled up our ability to make sense of it all. Researchers at the Earth Species Project (ESP), a nonprofit founded in 2018, recently used machine learning to detect carrion crow vocalizations and determine which bird made which call. ESP hopes its own Nature LM, trained on human speech, music, and animal sounds, will interpret the vocalizations of many species. That promise, however, is still theoretical. Tel Aviv University neuroecologist Yossi Yovel worries these models will overemphasize acoustic similarities and lump together sounds with different meanings.
As for a two-way conversation? It’s not clear when, or whether, that will happen. Still, “a lot of animals have an evolutionary structure that is similar enough that we should be able to understand what they’re saying,” Slobodchikoff says.
Source: MIT Technology Review · Summarized by HeadlinesBriefing