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1 | Title | URL | Description | Paid or free | Code available | License | Taxonomic or sound type specialization, if any | Ecosystem specialization, if any | Specific Hardware | Type | Data exploration | Organization | Annotation | Sound processing features | Acoustic index measurement | Acoustic feature measurement | Localization | Detector features | Classifier features | Comments | Publication URL | |
2 | acoupi | https://github.com/acoupi/acoupi | Open-source Python framework for deploying bioacoustic AI models on edge devices | Free | Yes | GPL v3 | Command line, Python | Real-time wireless messaging | Sqlite database, file naming, API network endpoint for third-party application, MQTT and HTTP communication protocol | AI-based model processing, can be adapted by configuration settings from user | ||||||||||||
3 | acoustic_indices | https://github.com/patriceguyot/Acoustic_Indices | calculate acoustic indices | free | Y | GPL v3 | Python | extract acoustic indices to use as biodiversity proxy | ||||||||||||||
4 | Adobe Audition | https://www.adobe.com/products/audition.html | geared toward sound editing | paid | N | desktop GUI | general-purpose audio review | edit audio | ||||||||||||||
5 | Anabat Insight | https://www.titley-scientific.com/product/anabat-insight/ | recording organization, review, and classification | free and paid versions | N | bats | terrestrial | desktop GUI | browse and view files as spectrograms | view labels on built-in maps | filter and process files with time expansion, pitch shift, etc. | calculate pulse and pass acoustic parameters, e.g. max frequency | use for bat call detection and custom filtering in full-spectrum and zero-crossing recordings | create decision tree classifiers and support third-party ID algorithms | ||||||||
6 | Animal Sound Identifier | https://datadryad.org/stash/dataset/doi:10.5061/dryad.221mq23 | classify animals using training data directly from field recordings, without reference libraries | free | Y | cc0 | birds | terrestrial | MATLAB | create cross-correlation classifiers; semi-active learning approach to create classifiers with little initial training data | https://onlinelibrary.wiley.com/doi/full/10.1111/ele.13092 | |||||||||||
7 | ANIMAL-SPOT | https://github.com/ChristianBergler/ANIMAL-SPOT | Python framework for building deep learning classification models | free | Y | GPL v3 | GPU recommended but not required | Python | use for binary target sound vs noise detection | create ResNet18 CNN classifiers | https://www.nature.com/articles/s41598-022-26429-y | |||||||||||
8 | APLOSE | https://osmose.ifremer.fr/app/ | web-based annotation tool for marine bioacoustics | free | Y | GPL v3 | marine wildlife | marine | web GUI | visualize spectrogram and adjust sound speed | create labels and boxes on spectrogram | https://www.sciencedirect.com/science/article/pii/S2352711025000226 | ||||||||||
9 | ARBIMON | https://arbimon.rfcx.org | web-based interface geared toward analyzing autonomous wildlife survey data | free | N | web GUI, phone app | listen and review autonomous recordings on GUI interface; create listening playlists | manage recorder deployment (phone app); web uploader that supports many common recorder timestamp formats | web-based annotation GUI | aggregate recordings at different temporal and spatial scales | customize template-matching detection tool; supervised and unsupervised available | free storage | ||||||||||
10 | ARTWARP | https://soundanalysis.wp.st-andrews.ac.uk | estimate frequency sweeps and cluster-classify tonal sounds | free | N | tonal sounds (e.g. bottlenose dolphin whistles and killer whale calls); individual animal recognition | marine | MATLAB | identify frequency sweeps | create classifier of tonal sounds using ART neural network | ||||||||||||
11 | Audacity | https://www.audacityteam.org/download | simple, lightweight listening and spectrogram viewing, comparison, and manipulation | free | Y | GPL v3 | desktop GUI | view one or many recording waveforms or spectrograms at once | full suite of sound editing features | |||||||||||||
12 | audiomoth-scripts | https://github.com/nwolek/audiomoth-scripts | spectrogram visualization and AudioMoth-specific tools | free | Y | MIT | recordings collected from AudioMoth recorders | Y | command line | use bash scripts for a variety of spectrogram visualizations | use script to rename AudioMoth hex files to human-readable filenames | some of these scripts were designed for older audio moth firmware that create clips in hexadecimal format | ||||||||||
13 | audioset_soundscape_feats_sethi2019 | https://github.com/sarabsethi/audioset_soundscape_feats_sethi2019 | GitHub repo for using machine learned features for soundscape analyses | free | Y | Python | feature extractor based on VGGish CNN | https://www.pnas.org/doi/10.1073/pnas.2004702117 | ||||||||||||||
14 | Australian Acoustic Observatory Audio Similarity Search | https://search.acousticobservatory.org/ | A bioacoustic search tool using audio similarity search to query Australian Acoustic Observatory data | free | Y | MIT | Australian ecosystems | Web GUI | upload sound and use audio similarity search to find similar sounds within A2O data | |||||||||||||
15 | AVA | https://autoencoded-vocal-analysis.readthedocs.io/en/latest/index.html | segment vocalizations and train generative models of vocalizations | free | Y | MIT | Python | organize files for plotting and analysis | infer latent descriptions of animal vocalizations using variational autoencoders | segment audio for syllable-level analysis | https://elifesciences.org/articles/67855 | |||||||||||
16 | AVES | https://github.com/earthspecies/aves | self-supervised, transformer-based audio representation model for encoding animal vocalizations | free | Y | MIT | general and birds | Python | fine-tune pretrained audio representation model for bioacoustic detection tasks | fine-tune pretrained audio representation model for bioacoustic classification tasks | https://arxiv.org/abs/2210.14493 | |||||||||||
17 | AVGN | https://github.com/timsainb/avgn_paper | characterize animal vocalizations for dimensionality reduction, clustering, and assessing vocalization sequencing, corpus-building, and generating artificial vocalizations | free | Y | MIT | birds | Python | extract information about acoustic features using embeddings created by a generative adversarial network | additional resource: https://github.com/timsainb/AVGN | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008228 | |||||||||||
18 | AviaNZ | http://www.avianz.net/index.php | graphical user interface for organizing, analyzing, and classifying recordings | free | Y | GPL v3 | birds | terrestrial | desktop GUI | open sound files, listen to and visualize audio | manual annotation and segmentation | run wavelet detector | create CNN classifiers to finetune classify wavelet detections; pretrained classifiers for several species | |||||||||
19 | Avisoft-SASLab Pro | http://www.avisoft.com/sound-analysis | automated detection and cross-correlation classification | paid | N | desktop GUI | open sound files, listen to and visualize audio | create tailored metadatabase | sound parameter measurement and noise level measurement | find TDOAs via cross-correlation | use template cross-correlation for event detection | create classifiers using template cross-correlation | compatible with GIS applications for field survey map creation and georeferencing | |||||||||
20 | Banter | https://github.com/EricArcher/banter | package used to create hierarchical acoustic classifiers | free | Y | GPL v3 | R | create random forest classifiers for pre-detected events | https://onlinelibrary.wiley.com/doi/abs/10.1111/mms.12381 | |||||||||||||
21 | BatClassify | https://bitbucket.org/chrisscott/batclassify/src | segmentation and classification of ultrasonic sounds | free | Y | GPL v3 | UK bat species | terrestrial | desktop GUI | run audio through pretrained bat classifiers | ||||||||||||
22 | BatDetect | https://github.com/macaodha/batdetect | bat detection in full-spectrum recordings | free | Y | CC BY 4.0 | bat echolocation calls | terrestrial | Python | use bat echolocation call detector for full-spectrum (i.e., not zero-crossing) recordings | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005995 | |||||||||||
23 | BatExplorer | https://www.batlogger.com/en/downloads/batexplorer/ | organize, annotate, detect, and classify bat call recordings | free and paid versions | N | can process bat logging data from BATLOGGER brand recorders (and others) | terrestrial | Y | desktop GUI | summarize data | organize bat call projects | listen to time-stretched ultrasonic recordings | automatic detection | pretrained classifier for UK & European bat species | ||||||||
24 | BatScope | https://www.wsl.ch/en/services-produkte/batscope/ | manage, sort, view, and play databases of recordings | free | N | bats | terrestrial | Y | desktop GUI | view and play audio files | pretrained classifiers of multiple types (SVM, neural network, etc.) for Swiss bat species | view GPS records of recordings | ||||||||||
25 | Bioacoustic F0 estimation | https://github.com/mim-team/bioacoustic_F0_estimation | Tool for estimating the fundamental frequency (F0) of non-human vocalizations | Free | Yes | GPL v3 | Command line, Python | Can export spectrograms overlaid with F0 predictions for users to visually check the results | Predicts the time, fundamental frequency (F0), and F0 contour of vocalizations | Detects any voices signal, can filter by F0 or F0 contour | The neural network provided in this tool was trained on diverse signals (e.g., dolphins, rodents, birds, lions) | https://doi.org/10.1080/09524622.2025.2500380 | ||||||||||
26 | bioacoustics | https://cran.r-project.org/web/packages/bioacoustics/index.html | sound filtering, automated detection, and extraction of acoustic features | free | Y | GPL v3 | R | read, display, and write audio files, including zero-crossing files | convert MP3, WAV, and WAC files | filter noisy files | extract acoustic features for further analysis | |||||||||||
27 | Bioacoustics Cookbook | https://github.com/kitzeslab/bioacoustics-cookbook/tree/main | examples of common bioacoustic workflows in Python | free | Y | MIT | Python, Jupyter Notebook GUI | calculate sunrise and sunset times at coordinate locations, review spectrogram grids | filter audio files to include only specific date ranges, convert between UTM and lat/long coordinates | review and annotate audio clips based on classifier scores and metadata in Jupyter Notebook | use pretrained audio feature extractor | train machine learning model, train shallow classifier, generate embeddings | ||||||||||
28 | Bioacoustics in Python | https://github.com/leabouffaut/bioacoustics_python | examples of common bioacoustic tasks in Python | free | Y | MIT | Python | load and manipulate Raven selection tables | resample audio files and create spectrograms | evaluate model performance | ||||||||||||
29 | Bioacoustics Model Zoo | https://github.com/kitzeslab/bioacoustics-model-zoo | collection of pretrained models for bioacoustic classification tasks | free | Y | Python | use MixIT Bird sound source separation model to separate audio into channels potentially representing separate sources | create embeddings for audio data using 3 common bioacoustic classifiers (Perch, BirdNET, HawkEars) | run 3 common bird sound classifiers (Perch, BirdNET, HawkEars) | |||||||||||||
30 | BioCPPNet | https://github.com/earthspecies/cocktail-party-problem | convolutional neural network-based architecture for bioacoustic source separation | free | Y | train classifier model and train separator model | https://www.nature.com/articles/s41598-021-02790-2 | |||||||||||||||
31 | BioLingual | https://github.com/david-rx/BioLingual | sound classification and retrieval using natural text queries | free | Y | Apache v2 | Python | use text-to-audio search | create zero-shot bioacoustic classifier using text | Also includes AnimalSpeak dataset | https://arxiv.org/abs/2308.04978 | |||||||||||
32 | BirdNET | https://github.com/kahst/BirdNET-Analyzer | pretrained classifier for birds | free | Y | MIT and CC-BY-NC-SA | 6000 bird species and some other species | terrestrial | command line, Windows GUI | run pretrained convolutional neural network classifier for 3000 bird species | ||||||||||||
33 | BirdVoxClassify | https://github.com/BirdVox/birdvoxclassify | pretrained nocturnal flight call classifier | free | Y | MIT | North American bird nocturnal flight calls | terrestrial | command line, Python | run pretrained classifier for North American bird nocturnal flight calls | https://www.justinsalamon.com/uploads/4/3/9/4/4394963/cramer_taxonet_icassp_2020.pdf | |||||||||||
34 | BirdVoxDetect | https://github.com/BirdVox/birdvoxdetect | machine learning-based detection for nocturnal flight calls | free | Y | MIT | North American bird nocturnal flight calls | terrestrial | command line, Python | run machine learning-based system to detect continuous nocturnal flight calls | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214168&type=printable | |||||||||||
35 | CARACAL | https://github.com/OpenWild/caracal | acoustic localization software geared toward CARACAL recorder | free | Y | MIT | geared toward multi-channel CARACAL recorder | terrestrial | Python | separate sound from source for time-synchronized DOA arrays | estimate direction of arrival to a single station and position estimates based on DOAs from multiple stations | detect and match sounds across recordings for acoustic localization | published alongside CARACAL four-microphone hardware; see here: https://www.tandfonline.com/doi/abs/10.1080/09524622.2019.1685408 | |||||||||
36 | CASE | https://www.mdpi.com/2076-2615/12/16/2020 | extract audio features, cluster, and analyze sound events | free | Y | Copyright with redistribution allowed | MATLAB GUI | extract features of animal sounds | use clustering and similarity detection algorithms for unsupervised classification | |||||||||||||
37 | categorizing_soundscapes | https://github.com/lifewatch/categorizing_soundscapes/tree/main | collection of jupyter notebooks to categorize and characterize soundscapes | free | Y | marine | Python notebooks | characterize sound environments using unsupervised clustering on dimensionally reduced summary values of spectrograms | also includes explainable random forest classifier to identify environmental covariates that predict sound environment | |||||||||||||
38 | CDSE | https://github.com/sys-uos/CDSE | Classifier-guided bird signal separation | Free | Yes | GPL v3 | Command line, Python | View continuous time series for bird species' vocalizations instead of discrete classification windows | Sound source separation | None (requires clasification results as input) | ||||||||||||
39 | Chirpity | https://chirpity.mattkirkland.co.uk | Desktop program for analyzing audio files with BirdNET and a nocturnal migration machine learning model | Free and paid versions | Yes | CC-BY-NC-SA | European nocturnal flight call (NFC) classification, BirdNET global bird classification | Desktop GUI, Browser GUI | Charts, graphical interface for viewing spectrograms, and data export to CSV, Raven, and Audacity label files | Database management for records and to compress/organise audio library | Graphical interface for annotating spectrograms and reviewing, correcting, and labelling IDs | Convert between filetypes, filter and process audio (gain, normalise, highpass, low shelf) | CNN classifiers for BirdNET and European Nocturnal Flight Calls/nocmig | |||||||||
40 | crowsetta | https://github.com/vocalpy/crowsetta | package for working with and translating between annotation formats | free | Y | BSD | Python | port between annotation data types, analyze annotations with python scripts | ||||||||||||||
41 | DAS | https://github.com/janclemenslab/das | method for automatically annotating song from raw audio recordings based on a deep neural network | free | Y | Apache-2.0 | geared toward segmenting laboratory animal vocalizations | captive animals | Python, command line, desktop GUI | create and edit annotations manually or automatically | train neural network to segment audio based on annotated sounds | unsupervized classification of songs | https://elifesciences.org/articles/68837 | |||||||||
42 | DAS4Whales | https://github.com/DAS4Whales/DAS4Whales?tab=readme-ov-file | Python package to analyze Distributed Acoustic Sensing (DAS) data for marine bioacoustics | free | Y | CC BY-NC-SA 4.0 | whales | marine | Python | read metadata and print information about spatial arrangement of distributed sensing array data | filter (e.g. bandpass, frequency-wavenumber domain) | https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.901348/full | ||||||||||
43 | DeepSqueak | https://github.com/DrCoffey/DeepSqueak | Using Machine Vision to Accelerate Bioacoustics Research | free | Y | BSD | originally intended for laboratory animal vocalization research | captive animals | MATLAB, GUI | visualize and annotate detections | use pretrained, retrainable, and trained-from-scratch detectors | |||||||||||
44 | DetEdit | https://github.com/MarineBioAcousticsRC/DetEdit | visualize and annotate detections | free | Y | Copyright (non-commercial permitted) | stereotyped impulsive signals (e.g. odontocete echolocation, human impulsive noise, fish, crustaceans) | marine | desktop GUI | visualize and annotate detections | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007598 | |||||||||||
45 | ecoSound-web | https://ecosound-web.de/ecosound_web/ | web application to manage, visualize, annotate and analyze soundscape recordings | contact for access, recording storage may not be free | Y | GPL v3 | desktop GUI | visualize and annotate detections | amplify, re-sample, split, filter, and compress audio | calculate acoustic indices to measure spectral, temporal and amplituidinal properties | ||||||||||||
46 | Ecosounds | https://www.ecosounds.org | website to manage, access, visualize, and analyze environmental acoustic data from repository | free (including storage) | N | ecoacoustic data | web GUI | correct timestamps, check for errors and provide error reports, annotate spectrograms | use any analysis software | |||||||||||||
47 | fieldtools | https://github.com/nilomr/fieldtools | plan deployments and copy/format large numbers of SD cards simultaneously | free | Y | MIT | command line | format large number of SD cards simultaneously | check data about recorder deployment and generate .gpx files | |||||||||||||
48 | gibbonR | https://github.com/DenaJGibbon/gibbonR-package | train neural networks, GMMs, and others | free | Y | R | extract audio features | run SVM and band-limited energy detector | create random forest and SVM classifiers using MFCCs | https://arxiv.org/abs/1906.02572 | ||||||||||||
49 | GlassOFire | http://www.oldbird.org/glassofire.htm | Windows software for avian nocturnal flight call review and sorting | free | N | avian nocturnal flight calls | terrestrial | desktop GUI | use GUI for reviewing and organizing avian nocturnal flight call detections | |||||||||||||
50 | GoldWave | https://www.goldwave.com | general-purpose audio software | free and paid versions | N | desktop GUI | view and manipulate audio | |||||||||||||||
51 | hardRain | https://github.com/Cdevenish/hardRain | detect rain sounds | free | Y | GPL v3 | rain | terrestrial | R | detect rain in audio recordings | https://www.sciencedirect.com/science/article/abs/pii/S1470160X19307873 | |||||||||||
52 | HARKBird | https://sites.google.com/view/alcore-suzuki/home/harkbird | acoustic localization software | free | Y | CC BY-SA | DOA arrays | terrestrial | Python | use tool for editing and annotating results of sound source separation | localize and separate sound sources | created compatible Raspberry Pi node for field recording | ||||||||||
53 | HawkEars | https://github.com/jhuus/HawkEars | classification of 314 bird species of Canada | free | Y | MIT | 328 bird songs | terrestrial | Python interface | scan audio and generate labels for audio files | classify sounds of 314 Canadian bird species and common confusion species (e.g. frog species) or create your own classifier | also available in Bioacoustics Model Zoo | ||||||||||
54 | hybrid-vocal-classifier | https://github.com/vocalpy/hybrid-vocal-classifier | automated labeling geared towards individual syllable identification | free | Y | BSD | vocal learning in captive animals | captive animals | Python | create nearest neighbor classifiers for intraspecific individual syllable identification | ||||||||||||
55 | INSTINCT | https://github.com/DanWoodrich/INSTINCT | bioacoustic pipelining software | free | Y | MIT | only set up for Windows | Python | utilitze pipeline for bioacoustic software | |||||||||||||
56 | Ishmael | https://repository.library.noaa.gov/view/noaa/11056 | marine sound detection and localization | free | N | marine wildlife | marine | desktop GUI | record in real-time | create annotations | localize sounds and localize specifically with beamforming | detect energy sum, spectrogram correlation, train for repetitive calls, detect whistle and moan, ROCCA click and whistle ID | ||||||||||
57 | Kaleidoscope | https://www.wildlifeacoustics.com/products/kaleidoscope-pro | software for detection via clustering with pretrained bat classifiers | paid, 15-day free trial | N | wide range of animals, but pretrained classifiers only available for bats | desktop GUI | manually identify and review clusters genererated by software | run pretrained bat classifier for bats of North America, U.K., Europe, Neotropics and South Africa | |||||||||||||
58 | KETOS | https://meridian.cs.dal.ca/2015/04/12/ketos | acoustic data analysis with neural networks | free | Y | GPL v3 | underwater acoustics | marine | Python | create neural network classifiers | ||||||||||||
59 | Koe Bioacoustics Software | https://koe.io.ac.nz | web-based acoustic data management and detection platform | free | Y | GPL v3 | acoustic units, especially in birds | terrestrial | web GUI | visually review and annotate detections | assess song sequence structure | use ordination plots to cluster and annotate groups of sound units | ||||||||||
60 | koogu | https://github.com/shyamblast/Koogu/tree/v0.6.5 | Python software wrapping around TensorFlow to create flexible deep learning models | free | Y | GPL v3 | Python | pre-process and transform audio | create flexible deep learning models via TensorFlow | |||||||||||||
61 | librosa | https://librosa.org/librosa | general-purpose sound analysis scripting toolkit | free | Y | ISC | Python | use all-purpose audio scripting features including loading, spectrogram generation | extract features like beat, tempo | apply temporal segmentation | ||||||||||||
62 | Luscinia | https://rflachlan.github.io/Luscinia | bioacoustic archiving, measurement, and analysis | free | Y | desktop GUI | manage database and archive records | measure acoustic signals as contours with dynamic time warping algorithm | ||||||||||||||
63 | MANTA | https://bitbucket.org/CLO-BRP/manta-wiki/wiki/Home | enables comparison between soundscapes from disparate datasets and identification of ambient ocean sound trends | free | Y | GPL v3 | geared towards marine bioacoustics | marine | GUI, MATLAB, executable | measure processing metrics such as SPL percentiles, frequency bandwidth, etc. as recommended by three international workshops focused on ocean soundscape and long-term trend data | ||||||||||||
64 | Mice-USVs-segmentation-and-classification | https://github.com/DiogoMPessoa/Mice-USVs-segmentation-and-classification | MATLAB interface to segment and classify mice ultrasonic vocalizations (USVs) | free | Y | mouse ultrasonic vocalizations | captive animals | MATLAB | automatically segment USV's based on spectral entroy | use classifier with hand-selected features (e.g. time, frequency, contour), unlike deep learning where features are determined automatically | https://pubs.aip.org/asa/jasa/article/152/1/266/2838328/Automatic-segmentation-and-classification-of-mice | |||||||||||
65 | monitoR | https://cran.r-project.org/web/packages/monitoR/index.html | automated detection via template matching | free | Y | GPL v2 | R | use template matching for detections | https://drive.google.com/file/d/1wmcs0UgSs8OG2cOcD8v7f2ckx8q9-UWB/view | |||||||||||||
66 | MUPET | https://github.com/mvansegbroeck/mupet | Matlab-based tool to analyze the ultrasonic calls emitted by mice | free | Y | Apache License 2.0 | mouse ultrasonic vocalizations | captive animals | GUI; Matlab | utilize tools for grouping recordings, e.g. by individual | measure acoustic features such as power spectrum, syllable rate | https://www.sciencedirect.com/science/article/pii/S0896627317302982 | ||||||||||
67 | NARW_detection_tool | https://git-dev.cs.dal.ca/meridian/NARW_detection_tool | command-line interface tool to streamline development of acoustic deep learning models for North Atlantic right whale (NARW) | free | Y | GPL v3 | North Atlanic right whale | marine | command line interface | create training and test datasets from raw acoustic data | train deep learning model to detect NARW vocalizations | https://publications.gc.ca/collections/collection_2019/mpo-dfo/Fs97-6-3345-eng.pdf | ||||||||||
68 | NightHawk | https://github.com/bmvandoren/Nighthawk/ | machine learning tool for classifying avian nocturnal flight calls | free | Y | CC BY-NC v4.0 | North American avian flight calls | terrestrial | command line interface or use with Vesper GUI | classify bird nocturnal flight calls | https://www.biorxiv.org/content/10.1101/2023.05.22.541336v1 | |||||||||||
69 | Ocenaudio | https://www.ocenaudio.com | general-purpose audio editing software | free | N | GUI | view waveform and spectrogram | adjust sound amplitude, apply effects | ||||||||||||||
70 | ohun | https://marce10.github.io/software/ohun/ | automated detection of acoustic signals with tools for diagnosing detector effectiveness | free | Y | GPL v2 | R | use energy- and template-based detection; and utilize tools to evaluate detection performance | ||||||||||||||
71 | OpenSoundscape | http://opensoundscape.org | software ecosystem for analyzing bioacoustics recordings, training, and applying convolutional neural network classifiers | free | Y | MIT | any sound; specific tool for classification of repeating sounds (e.g. trills) | Python | process Raven sound software annotation files | manipulate audio, e.g. bandpass and sound augmentation for convolutional neural network training | localize from synchronized recording arrays | use signal processing for sounds with repeating structure (e.g. trills) | create a wide variety of deep learning networks for classification of animal sounds; parallelize classification over CPUs or GPUs | https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.14196 | ||||||||
72 | PAMguard | https://www.pamguard.org | graphical interface for creating acoustic pipelines for sound analysis, classification, and detection. Has a large userbase that creates and shares plugins | free | Y | GPL v3 | marine and cetacean; specific tools for some taxa | marine | desktop GUI | visualize spectrograms | organize sensor locations | use a wide variety of sound processing applications, e.g., amplification, noise reduction, spectrogram creation | measure acoustic parameters with a wide variety of plugins, e.g. envelope tracing, LTSA | localize sounds using a wide variety of methods, e.g., direction of arrival (bearing), multipath 3D localization, Ishmael | detect a wide variety of marine sounds, e.g., clicks, whistles, species-specific sounds | classify sounds with a wide variety of plugins, e.g. pretrained whistle classifiers, template matching, deep learning | very long-lived and continuously maintained modular software; for more info on available plugins see here: https://www.pamguard.org/coremodules.html | |||||
73 | PAMpal | https://github.com/TaikiSan21/PAMpal | compute acoustic features of PAMguard detections | free | Y | GPL v3 | marine wildlife | marine | R | compute acoustic features of PAMguard detections | Formerly known as PAMr | |||||||||||
74 | Parselmouth | https://github.com/YannickJadoul/Parselmouth | Python library for interacting with Praat annotation and acoustic parameter measurement functionality | free | Y | GPL v3 | Python | visualize spectrograms | integrate Praat annotation workflows into Python | apply wide array of Praat acoustic parameter measurement tools using Python | https://www.sciencedirect.com/science/article/abs/pii/S0095447017301389?via%3Dihub | |||||||||||
75 | Praat | https://www.fon.hum.uva.nl/praat | annotation and sound feature analysis; has been ported directly into Python (see Parselmouth) | free | Y | GPL v3 | individual sound analysis; originally intended for human phonetics | desktop GUI | annotate sounds from individual animals, e.g. for studies of vocal repertoire and learning | utilize wide variety of speech analysis tools, e.g. fundamental frequency analysis; spectral, pitch, formant, intensity analysis | https://www.fon.hum.uva.nl/paul/papers/speakUnspeakPraat_glot2001.pdf | |||||||||||
76 | prinia-project | https://github.com/shivChitinous/prinia-project | bird song note classification and analysis | free | Y | cc0 | bird songs | terrestrial | Python + MATLAB | analyze complexity and repetition rate for bird songs | create PCA, linear discriminant, and hierarchical clustering classifiers to classify song notes | https://academic.oup.com/beheco/article-abstract/31/2/559/5702188?redirectedFrom=fulltext&login=false | ||||||||||
77 | Pykanto | https://github.com/nilomr/pykanto | Python library and GUI for exploring and labeling audio for research on bird song units | free | Y | MIT | birds | primarily terrestrial | Python and GUI | visualize spectrograms | organize datasets | automatically segment sound | extract common acoustic features, e.g. bandwidth, min/max frequency | use automated segmentation | train convolutional neural network classifier | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008228 | ||||||
78 | PyPAM | https://github.com/lifewatch/pypam?tab=readme-ov-file | Python package to analyze underwater sound | free | Y | GPL v3 | marine wildlife | marine | Python | process audio from multiple deployments and extract features that can be used for ML algorithms | calculate acoustic indices | compute frequency domain analysis | package under active development, newer version removed detectors | |||||||||
79 | PyPorCC | https://github.com/lifewatch/pyporcc | Python package that detects and classifies clicks from Harbor Porpoises' | free | Y | MIT | Harbor Porpoises | marine | Python | detect clicks in continuous files as an adaptation of the PAMGuard click detector | classify porpoise clicks as high quality, low quality or high-frequency noise | https://pubs.aip.org/asa/jasa/article-abstract/145/6/3427/939421/Porpoise-click-classifier-PorCC-A-high-accuracy?redirectedFrom=fulltext | ||||||||||
80 | Raven Lite | https://ravensoundsoftware.com/software/raven-lite | general bioacoustic listening and annotation | free | N | desktop GUI | visualizw and play spectrograms | annotate sounds (only one notes column available in free version) | measure power and other basic acoustic features | very long-lived, continuously maintained software; .selections.txt annotation format able to be ported into many applications | ||||||||||||
81 | Raven Pro | https://ravensoundsoftware.com/software/raven-pro | general bioacoustic listening and annotation | paid; reduced-price options | N | desktop GUI | visualizw and play spectrograms | annotate sounds | measure power and other basic acoustic features | use template-matching, band-limited energy detector | ||||||||||||
82 | Reaper | https://www.reaper.fm | spectrogram visualization | free and paid versions | N | desktop GUI | spectrogram visualization; enables Python and C/C++ coding within | extract features like beat, tempo | ||||||||||||||
83 | scikit-maad | https://github.com/scikit-maad/scikit-maad | general-purpose machine learning package | free | Y | BSD | Python | compute acoustic indices | compute acoustic features; estimate SPL | segment audio based on user-provided frequency and length parameters | https://www.sciencedirect.com/science/article/abs/pii/S1470160X1830181X?via%3Dihub | |||||||||||
84 | scipy.signal | https://docs.scipy.org/doc/scipy/reference/signal.html | general signal processing algorithms | free | Y | BSD | Python | generate spectrograms | estimate time delays using spectrogram cross-correlation (scipy.signal.correlate) | use to implement template-matching using spectrogram cross-correlation | Subpackages cover extensive scientific computing domains | |||||||||||
85 | SDEer | http://dx.doi.org/10.6084/m9.figshare.3792780 | direction-of-arrival estimation | free | Y | CC-BY | MATLAB | manually annotate for acoustic localization | localize using recording synchronization and DOA estimation | use several detection algorithms | ||||||||||||
86 | seewave | https://cran.r-project.org/web/packages/seewave/index.html | general acoustics toolbox | free | Y | GPL v3 | R | display spectrograms | compute signal envelopes | compute cross-correlation | ||||||||||||
87 | SongExplorer | https://github.com/JaneliaSciComp/SongExplorer | deep learning for segmenting acoustic signals | free | Y | BSD 3-Clause and Apache License 2.0 | browser GUI, Python | utilize workflow for discovering sounds | annotate audio in graphical interface | train deep learning algorithm to segment animal sounds | https://www.biorxiv.org/content/10.1101/2021.03.26.437280v1 | |||||||||||
88 | SonicVisualizer | https://www.sonicvisualiser.org | spectrogram visualization | free | Y | GPL v2 | desktop GUI | visualize spectrograms | annotate audio in graphical interface | https://www.sonicvisualiser.org/sv2010.pdf | ||||||||||||
89 | SonoBat | https://sonobat.com | classification of bat calls | paid | N | bats | terrestrial | desktop GUI | batch edit metadata notes | use "compressed view" of detections | run pretrained classifier for North American bats using extracted acoustic features | |||||||||||
90 | Sound Finder | https://github.com/rhine3/pysoundfinder?tab=readme-ov-file | position estimation | free | Y | CC-BY-NC-SA | R, Excel | estimate position using GPS algorithm that takes pre-calculated TDOAs as inputs | https://www.tandfonline.com/doi/abs/10.1080/09524622.2013.827588 | |||||||||||||
91 | Soundata | https://soundata.readthedocs.io/en/latest | load and work with audio data | free | Y | BSD | Python | load and work with audio datasets in a standardized way | support annotations with confidence levels | |||||||||||||
92 | Soundbay | https://github.com/deep-voice/soundbay | Python framework for building and applying deep learning models for bioacoustics | Free | Yes | AGPL-3.0 | implemented for marine mammals, should work for any signal | implemented for marine mammals, should work for any signal | Python | Scripts and classes for data processing and loading for deep learning models | Deep learning-based detection | Deep learning-based classification | ||||||||||
93 | soundClass | https://github.com/bmsasilva/soundClass | audio annotation and training and prediction with neural network classifiers in R | free | Y | GPL v3 | R | create SQL database of recordings | annoate files in GUI | train and predict with CNNs | the CNN architecture used is small, in order to make training computationally feasible in R | https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13964?af=R | ||||||||||
94 | soundecology | https://cran.r-project.org/web/packages/soundecology/vignettes/intro.html | calculate soundscape-wide acoustic indices | free | Y | GPL v3 | R | calculate acoustic indices | ||||||||||||||
95 | Soundgen | http://cogsci.se/soundgen.html | open-source toolbox for voice synthesis, manipulation, and analysis | free | Y | GPL v3 | R | visualize spectrograms | manipulate and synthesize sound | https://pubmed.ncbi.nlm.nih.gov/30054898/ | ||||||||||||
96 | soundscape_IR | https://github.com/meil-brcas-org/soundscape_IR | python-based toolbox of soundscape information retrieval | free | Y | MIT | Python | visualization of soundscape dynamics | train model for audio source separation | https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13960 | ||||||||||||
97 | SoundScapeExplorer | https://sound-scape-explorer.github.io/ | interface for sampling recordings and extracting soundscape/CNN features from them | free | Y | MIT | Web GUI | visualize audio and results from soundscape analysis, including dimensional reduction of neural network outputs | extract audio at desired sampling interval | extract several acoustic features and neural network embeddings | ||||||||||||
98 | SoundScope | https://github.com/xaviermouy/SoundScope | visualization and manual verification of detections from automated detectors | free | Y | BSD 3-Clause | whale and fish | geared toward marine environments | GUI through Python | visualize detections from sound detectors | verify or annotate automatic detections using a GUI | |||||||||||
99 | SoundSort | https://github.com/macster110/aipam | visualize, cluster, and annotate annotations | free | Y | GPL v3 | desktop GUI | visualize and annotate recordings, then export these annotations | cluster similar pre-detected clips | "Note that SoundSort is on ice untill a project requires it's use again - please get in contact if you would like any more info" | ||||||||||||
100 | Sox-o-matic | https://www.birds.cornell.edu/ccb/sox-o-matic | facilitates file management by simplifying the process of compressing, converting, and renaming audio files | free | N | Copyright (permissive use) | desktop GUI | rename audio files | convert between filetypes, compress audio |