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Project # 50
Decoding the "Meow": Semantic Analysis of Feline Vocalizations
| Team Lead: | Hridayesh Lekhak |
| Other Team Members: | |
| Faculty Advisor(s): | Dr. Kenny Zhu |
| Department: | CSE |
| Project Type: | REU |
| Title: | Decoding the "Meow": Semantic Analysis of Feline Vocalizations |
| Abstract: | Domestic cats occupy a unique position as one of humanity's most prevalent companion animals, yet the mechanisms underlying their communicative behaviors remain poorly understood. While cats vocalize frequently, it is unverified whether they encode specific semantic meanings or modify vocal patterns based on their audience. Building on an existing dataset of approximately 100 hours of curated cat vocalizations from prior lab research, this project utilizes Vision Language Models (VLMs) for situational context extraction and Self-Supervised Learning (SSL) models (e.g., HuBERT) to identify acoustic patterns. The primary goal is to determine if cats exhibit vocal plasticity across different interaction modes: Cat- Human, Cat-Cat, and Cat-Alone. |
| Poster: | View Poster #50 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |