Decoding Communication in Nonhuman Species II (2023)
2023-06-07..2023-06-13
Berkeley, United States
who it's for
animal communication researchers, bioacoustics engineers, computational ethologists, machine learning researchers, field biologists, conservation technologists, computer vision researchers, neuroethologists
topics
dolphin signature whistle classification; sperm whale coda language models; masked acoustic token modeling; hierarchical residual VQ-VAE SoundStream; explanatory learning with conjecture interpreter; emergent communication games with transformers; structural transfer learning for syntax; vocal labeling in African elephants; GPS and sensors for hyena coordination; generative adversarial articulatory models; dataset scale effects in computer vision; audio style transfer from small data
| title | author | length |
|---|---|---|
| Explanatory Learning: Unleashing New Knowledge in Unknown Languages | Antonio Norelli, Emanuele Rodolà | 01h 08m |
Claims a machine can learn to read and write explanations by training two transformer modules—a conjecture generator and an interpreter—under the Explanatory… | ||
| Music Generation via Masked Acoustic Token Modeling | Bryan Pardo | 58m |
Combines parallel iterative decoding with discrete acoustic token modeling to generate and infill music audio; uses SoundStream and a hierarchical residual… | ||
| Structural Transfer Learning: Exploring Neural Models and Language Structure Through... | Isabel Papadimitriou | 01h 01m |
Pretraining small transformer models (GPT-2 small) on synthetic symbolic data—nesting parentheses, crossing dependencies, a regular repeating control and… | ||
| Individual Discrimination of Bottlenose Dolphin Signature Whistles Using Deep Learning | Frants Jensen | 01h 01m |
Long-term Sarasota suction-cup recordings (38+ years, ~61,000 whistles; ~47,000 labeled signature whistles from ~295 individuals, 171 repeatedly) feed a… | ||
| Decoding Dolphin Communication | Diana Reiss | 57m |
Built an underwater keyboard (Apple II era, fiber optics) and finds dolphins imitate computer whistles after very few exposures — e.g. 19 exposures for the… | ||
| Deep Emergent Communication: How It Started and How It’s Going | Roberto Dessi | 55m |
Presents concrete experiments where neural agents play a communication game (sender generates discrete messages, receiver points to the target) using… | ||
| GPT-Whale Language Models at Tools for Structure Discovery and Hypothesis Generation | Pratyusha Sharma, Jacob Andreas | 01h 04m |
Uses language-model black boxes trained on annotated sperm whale codas (about 3,840 codas) represented as discrete tokens (roughly 21–26 coda types) and… | ||
| Generative AI and What Is Meaningful Sperm Whale Communication | Gašper Beguš | 01h 03m |
Generative adversarial models get trained on raw sperm whale codas and researchers probe them with latent unit interventions (stretching single bits beyond… | ||
| Do Elephants Have Names? Vocal Labeling of Individual Conspecifics in African Elephants + ... | Michael Pardo | 57m |
Wild African elephant rumbles analyzed from Samburu and Amboseli (625 contact and greeting calls) show acoustic signatures that identify intended receivers: a… | ||
| Communication in the Service of Coordinated Action by Spotted Hyenas | Kay Holekamp | 43m |
A field project fits GPS collars, microphones, accelerometers and magnetometers to every member of a hyena clan and records GPS every second plus continuous… | ||
| Computer Vision after the Victory of Data | Alexei Efros | 01h 18m |
Argues that scale and concrete data choices — not clever algorithms alone — explain many breakthroughs: 80 million 32×32 images let simple nearest-neighbor… | ||
| nothing matches | ||