iNaturalist Sound Classifier

A browser extension to analyze sound recordings directly on iNaturalist observation pages. It runs state-of-the-art machine…

A browser extension to analyze sound recordings directly on iNaturalist observation pages. It runs state-of-the-art machine learning models locally in your browser to identify species from sound. --------------------------------------------------- What does it do? When you visit an iNaturalist observation page that contains a sound recording, this extension adds a panel that lets you run AI-powered bioacoustic analysis with a single click. It helps identifying which species are vocalizing, validates those detections against geographic occurrence data, and display ranked results with confidence scores. Whether you're a researcher or a citizen scientist, this tool can help improving sound-only data identification on iNaturalist. --------------------------------------------------- Key features -> Runs 100% locally All AI inference happens in your browser using WebAssembly. There are no accounts, no subscriptions, and no data collection. -> Geographic check The extension reads the observation's coordinates and automatically filters available models by region. After generating predictions, it cross-references every top detection against GBIF and iNaturalist species occurrence databases to tell you whether that species has been documented in that area. Detections are marked with a ✓ (within range) or ⚠ (outside known range), helping you distinguish likely IDs from unusual records. -> State-of-the-art models Comes pre-configured with two leading bioacoustic models: - BirdNET v2.4 (Cornell Lab of Ornithology) — trained on over 6,000 bird species worldwide, one of the most widely used bird sound classifiers in the world (size ~50MB) - Perch v2.0 (Google Research) — a broader-scope model covering animal vocalizations across taxonomic groups (size ~400MB) Both models are downloaded from huggingface on first use and cached locally, so subsequent analyses load instantly. -> Fully configurable - Adjust the confidence threshold to filter weak detections - Control the analysis window overlap for finer time resolution - Choose between softmax, sigmoid, or raw logit outputs - Export results as CSV for downstream analysis - Clear the model cache at any time from the settings panel -> Extensible: bring your own models Researchers and developers can add any ONNX classification model through the extension's model manager UI — no code changes required. Configure the model URL (huggingface or zenodo), sample rate, window size, label file, and activation function, and the extension will handle downloading, caching, and inference automatically. --------------------------------------------------- How it works 1. Navigate to any iNaturalist observation page that has a sound recording attached. 2. The extension panel appears automatically. Select a model from the list (filtered to models relevant to the observation's location). 3. Click Run Analysis. The model downloads on first use, then analysis begins immediately. 4. Audio is fetched from iNaturalist, decoded, resampled to the model's required sample rate, and split into overlapping time windows. 5. Each window is processed by the AI model running locally via ONNX Runtime WebAssembly. 6. Top predictions are validated against geographic occurrence data from GBIF and iNaturalist. 7. Results appear in ranked order with species names, confidence scores, time windows, and range validation status. 8. Optionally export results as CSV for further analysis in your tool of choice. --------------------------------------------------- Model licenses - BirdNET v2.4: CC BY-NC-SA 4.0 (Cornell Lab of Ornithology / Chemnitz University of Technology) - Perch v2.0: Apache 2.0 (Google Research) This extension is open source (GPL-3.0). Contributions and custom model configurations are welcome. --------------------------------------------------- Privacy This extension does not collect, transmit, or store any personal data. Audio is fetched directly from iNaturalist's public API (the same request your browser makes when you press play) and processed locally. The only outbound requests made are to iNaturalist and GBIF public APIs for species occurrence metadata, which contain no audio data. No analytics, no tracking, no third-party services.