# FGC2.3: Feline Vocalization Classification and Cat Translation Project

> Deep learning model and system classifying cat vocalizations into 40 categories

FGC2.3 is an audio classification system and deep learning model developed by Pattern of USA Inc. using CNN and LSTM architectures to classify feline sounds across 40 granular categories. Built on a dataset spanning food, life events, aggression, mating, and distress complaints, it achieves over 95% reported accuracy and powers a real-time cat vocalization translation app on iOS.

Website: https://researchgate.net/publication/392268092_FGC23_Feline_Vocalization_Classification_and_Cat_Translation_Project

## What it is for

- Translate cat meows and vocalizations into English phrases in real time
- Identify specific cat needs such as hunger, pain, discomfort, or mating behaviors
- Classify complex feline sound sequences and behavioral acoustic patterns for research

## Features

- 40 distinct vocalization classes across 5 behavioral categories: Food, Life, Fight, Sex, and Complaint
- Support for single sounds, repeated sound sequences (RS), and complex sound sequences (CSS)
- Deep learning architecture combining CNN and LSTM networks
- Over 95% classification accuracy on curated audio datasets
- Deployment in an iOS application for real-time mobile audio translation

## Pricing

Free. Research paper preprint available for free on ResearchGate

## Details

- Type: AI model
- Category: [AI](https://xiry.app/topics/ai.md)
- Open source: no
- Platforms: iOS, Web
- For: Pet owners, animal behaviorists, and AI audio researchers
- Alternative to: MeowTalk
- Tags: audio, cats, translation, cnn, lstm, bioacoustics, ios

## Why it was saved

- [@niickjackson, 30 June 2025](https://www.instagram.com/reel/DLgQv-7sDaL/): Aims to help pet owners understand their cats' needs (such as hunger or attention) with a reported 95% accuracy rate.

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Updated 3 October 2026. Page: https://xiry.app/resources/fgc2-3-feline-vocalization-classification-and-cat-translatio

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