Humanity has always wanted to talk to the animals. Now, artificial intelligence is beginning to listen. Across the globe, from backyard bird feeders to the deep ocean, researchers are deploying powerful AI to decode the languages of other species. The quest is fraught with technical challenges and ethical questions, but it is driven by a hope that understanding may be the key to survival.

This is Portland. An avid birder and AI developer posts a message on a tech forum in October 2025. He has built a model that listens to a human’s poor imitation of a bird call and, in return, produces the authentic sound. He describes it as a “speech-to-speech” tool, probably not for profit. He is looking for a zoologist to help him expand the work to dog barks and cat purrs.

The Rosetta Stone

Off the coast of Dominica, the work is on a different scale. Here, Project CETI—the Cetacean Translation Initiative—is trying to decode the language of sperm whales. Researchers deploy underwater microphones, drones, and non-invasive tags that record the clicks, known as “codas,” that whales use to communicate. This is not a project of imitation. It is a hunt for a blueprint, a Rosetta Stone for a non-human language. Their AI models analyze thousands of vocalizations, seeking patterns. They have found them. The whales’ clicks have a complex structure, with variations in timing and rhythm that researchers have called a “sperm whale phonetic alphabet”. The discovery suggests the information carried in their calls is far greater than once believed.

The Universal Model

A different group, the Earth Species Project, takes a broader approach. They are not focused on a single species. They aim to build a universal foundation model applicable across the Tree of Life. Their flagship model, NatureLM-audio, is trained on a vast and diverse dataset of bioacoustics, from crows to elephants. Their work has shown that AI models trained on human speech can find similar structures in animal communication, suggesting universal patterns may exist.

The public is eager for this connection. A global survey found that 70 percent of people want to know what animals are thinking and feeling. This has fueled a market for consumer devices. The Petpuls collar claims to analyze a dog’s bark and classify its emotion as happy, anxious, or sad. The MeowTalk app has been downloaded over 20 million times by cat owners hoping to translate their pet’s meows. These tools are not true translators. They are emotion classifiers, inferring intent from acoustic features. They highlight a vast gulf between guessing a pet’s mood and understanding a whale’s coda.

The Great Unknowns

The challenges are immense. True understanding requires colossal datasets that, for most species, do not exist. There is the risk of anthropomorphism, of hearing human-like language where there is only a complex system of signals. And there are profound ethical questions. The same public that shows intense curiosity also fears misuse and supports strict regulation of any commercial applications.

The Deeper Purpose

The drive to overcome these hurdles is not fueled by curiosity alone. It is propelled by the urgency of a global biodiversity crisis. The same AI that hunts for syntax in whale song is also deployed to monitor ecosystems, track endangered species, and combat poaching. Decades ago, the discovery of the humpback whale’s song helped spark the “Save the Whales” campaign. Today, the hope is that a deeper understanding will foster a deeper empathy. The quest is to move from mimicry to meaning, from monologue to dialogue. The ultimate goal of learning to listen is not just to understand the animals, but to save them.