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Pet Translator Apps? We’re Closer To Decoding Animal Language Than You Think


Dog owners will attest that we have Four-legged best friends They are very expressive creatures. For many of us, coming home after a long day of work involves wagging tails, happy jumps, or a series of playful barks and howls from our dogs. While the sentiment of “I’m glad you’re back” is conveyed, the nuances of the conversation, of course, get lost in translation.

The same can be said about human-animal interactions in the wild. Consider a hypothetical scenario in which you encounter a chimpanzee in its natural environment. Suddenly, he starts making loud, threatening noises and shows aggressive gestures. While we understand these signals as hostile based on a chimpanzee’s body language and vocalizations, the finer points of what he or she is expressing—be it fear, a territorial warning, a question, or a direct threat—remain unclear.

What if there was a way to “remove” yourself from a situation, just as you might try to de-escalate a confrontation with another human being?

Advances in machine learning are beginning to make such scenarios possible. There are now tools designed to sift through large data sets of animal sounds and actions to create a rudimentary dictionary of animal language. Here are two cases where we successfully deciphered what animals were saying.

1. Sperm whale language is being codified

Sperm whales, which are highly social animals, use a sophisticated system of clicking sounds called a coda to communicate with each other, much as humans use Morse code. These sounds are produced when these whales release air from their nasal passages.

Although we’ve been able to precisely associate distinct codes with the actual sperm whale that makes them, most aspects of its communication system were not yet understood — that is, until recently. Stady Published in Nature Communications Use AI to comb through nearly 9,000 codes and understand clicks.

Specifically, the study discovered new properties of the coda, which they called “rubato” and “ornamentation,” which change based on the context of the conversation and are constantly used and imitated among whales. Researchers have found that these codas use a system that blends rubato and ornamentation with fixed features – tempo and tempo – to create a wide range of distinct codas.

By analyzing these features using the brainpower of artificial intelligence, the researchers proposed a “sperm whale phonetic alphabet,” which is similar to our own International Phonetic Alphabet.

“Like the International Phonetic Alphabet of Human Languages, the Sperm Whale Phonetic Alphabet shows how a small set of axes of variation (place of articulation, articulation, and pitch in humans; tempo, tempo, ornamentation, and rubato in sperm whales) can give rise to a group A variety of observed phonemes (in humans) or codas (in sperm whales).”

2. “DeepSqueak” is like Google Translate for rodent noise

Rodents, including mice and rats, communicate using high-pitched ultrasonic vocalizations (USVs). These vocalizations are often at frequencies above the range of human hearing.

Humans can typically hear sounds up to about 20 kHz, while rodent sounds can range from 20 kHz to over 100 kHz, making them inaudible to us without specialized equipment. Study of these sounds, although non-invasive, was considered expensive and laborious until that time deepsquicka machine learning tool, was developed in 2018 to detect these high-pitched squeaks.

Speaking to DW, the lead researcher behind DeepSqueak, Kevin Covey says“AI and deep learning tools are not magic. They will not suddenly translate all animal sounds into English. The hard work is done by biologists who need to observe animals in many situations and correlate calls with behaviors, emotions, etc.

What the software does is simplify the research process by isolating rodent calls from raw audio, matching them with similar sounds and providing insight into the behaviors of these animals. It’s essentially a sophisticated translator, decoding the language of rodents’ ultrasounds into data that researchers can analyze.

Such examples, as we begin to understand communication between animals, are becoming increasingly common, illustrating the rapid development of our technological capabilities. Although still in its early stages, the feasibility of human-animal communication – both theoretically and practically – is becoming clear.

Today, we may not yet be able to chat freely with our pets, but consider this: Just a few years ago, advanced AI tools like ChatGPT seemed like futuristic dreams. Now, they have become part of our daily lives. This rapid progress suggests that meaningful dialogues with animals may soon be within our reach.



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