Trail Notebook: Birding Offline with BirdNET and Gemma

Description and use

A local-first birding journal that records trail audio, detects species with BirdNET, and writes AI-generated notes using Gemma3:4b, all offline.

Problem

Need a field journal that records bird sounds, detects species, and generates notes without uploading audio to external services.

Outcome

Offline pipeline that turns trail recordings into structured, AI-generated birding journals without external uploads.

Workflow

• Record bird song on phone
• Store audio file
• Run trail_notebook.py with --browse to select recording
• BirdNET (via birdnetlib) analyzes audio locally
• Ollama runs Gemma3:4b to generate journal based on BirdNET detections
• Save output as Markdown file named after recording

Evidence

BirdNET identifies candidate bird calls. Then a local language model turns those detections into a short journal entry, saved as Markdown with a species table, confidence scores, and timestamps.

Source

Processing them locally means I don’t have to upload them to a service I don’t control.

Source

BirdNET can misidentify calls, especially in noisy recordings. Confidence scores are useful context, not proof, so detections should be checked against the recording and the generated journal should be reviewed.

Source