Chirpity: Identify Birds by Sound
Using Machine Learning to identify bird calls in audio recordings
Welcome to Chirpity, your ultimate companion for identifying bird vocalisations. Designed with Nocmig enthusiasts and bioacoustic researchers in mind, Chirpity revolutionises the process of reviewing extensive audio files for the presence of avian sounds. Powered by cutting-edge Machine Learning, Chirpity offers the choice between the well-known BirdNET and a bespoke Nocmig model - finely tuned for Nocturnal Flight Calls - ensuring identification tailored to your specific needs. With intuitive features for reviewing, tagging, and organizing detected calls, Chirpity saves valuable time and effort. Available for Windows, Mac and Linux platforms, download Chirpity today!
Key Features
- Compare with reference calls: Compare any species detection with reference calls sourced from xeno-canto , sorted by call type.
- Broad file format support: Supports WAV files including 32bit float PCM, those output by many commonly used recorders including: AudioMoth, Zoom, Tascam and Sound Devices. You can also analyse compressed files including: MP3, MP4/M4A, AAC, Opus, Ogg and FLAC
- New! Support for GUANO metadata: If GUANO metadata is embedded in the file, this is read, and the recording location and timestamp are set automatically
- In-built Archive: Save detections to an archive database for future reference and retrieval. Compress and organise original recordings into an audio library
- Multilingual Support: Display bird names in 28 languages, including German, Spanish, French and Japanese. Chirpity introduces UK English names for BirdNET detections.
- Custom lists: Limit reported detections to birds in your location at the time of year, birds active at night, or provide a custom list to specify precisely the species of interest to you.
- Background Analysis: Analyze audio in the background while you continue to explore the timeline.
- Retrospective adjustment: Adjust the detection list or confidence threshold either before or after analysis.
- Save and Export: Save detections, export audio clips, and customise formats and quality.
- eBird Compatibility: Export detections in eBird Record format.
- Enhance Sensitivity: Highlight and analyze specific segments for more sensitivity.
- Enhance audio: Audio filters allow you to adjust background noise.
- Easily Refine Results: Update the details of records, amend or delete them. Add records manually.
- Charts: View charts of saved records. Visualise the change in numbers of species' detections through the season.
- Locations: Set custom recording locations, filter saved records by species, location, date and time.
Performance Comparison
Many people familiar with BirdNET have used the "BirdNET Analyzer GUI" for automated bird call identification. Due to many optimisations made in the application, Chirpity is able to perform the analysis significantly faster. The following benchmark data show the time taken to analyse a file just over 3 hours long. Firstly using the native Chirpity detection model, then BirdNET within Chirpity, and finally BirdNET using the BirdNET Analyzer. The number in brackets shows how much faster than real-time this represents:
| Model | App Launch | Core i5 CPU | Core i5 GPU | M2 CPU | M2 WebGPU |
|---|---|---|---|---|---|
| Chirpity native | < 3s | 80s (140x) | 28s (388x) | 67s (167x) | 44s (252x) |
| Chirpity BirdNET | < 3s | 106s (106x) | 270s (41x) | 75s (148x) | N/A |
| BirdNET Analyzer | > 100s | 549s (20x) | N/A | 126s (88x) | N/A |
Downloads (
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First released to the public on February 8th, 2024, Chirpity already has regular users in 15 countries and counting!
Release history
Video Walkthrough (best viewed fullscreen)
An introductary tour of the key features of Chirpity.