soundscape

A library for soundscape synthesis and augmentation

Soundscape analysis with BirdNET.

This is an audio application that produces 3D binaural audio from 2D mono audio samples and positional information given by the graphical user interface. Listen to 3D audio through stereo headphones. Video Demo:https://www.youtube.com/watch?v=peF9cZSwVGw

Phanary is a lightning-fast, free, online app for desktop and mobile that excels at finding and playing atmospheric music and sound effects for games like D&D and Pathfinder. Phanary is meant to be used in a Game Master's preparation and improvisation, and to be quick and streamlined enough to smoothly handle the party going somewhere unexpected.

Tools of soundscape information retrieval, this repository is a developing project. Please go to https://.com/meil-brcas-org/soundscape_IR for full releases.

A Java audio-playback class, modeled on javax.sound.sampled.Clip, enhanced with concurrent playback and dynamic handling of volume, pan and frequency. Maven version.

Moved to new location https://gitlab.com/pab44/3d-audio-producer .Application to produce 3d audio (binaural or surround sound) with a graphical user interface and mono audio files.

An open toolbox of soundscape information retrieval

An iOS application/service that aids navigation through spatialized audio

Unsupervised classification to improve the quality of a bird song recording dataset. https://doi.org/10.1016/j.ecoinf.2022.101952

Web application for ecoacoustics to manage, navigate, visualise, annotate, and analyse soundscape recordings.

Desktop soundscape application

A more powerful, intuitive, and concurrency safe Clip, for Java audio needs.

Workflow Integration-Tools for the user community of d&b Soundscape.

Process ocean audio data archives to daily analysis products of hybrid millidecade spectra using PyPAM.

Ashdeck is open source productivity app for blocking distractions and boasting focus.

A Flask app to generate soundscapes from pictures and videos

Deep neural network model combining audio signal processing and pre-trained audio CNN achieved 90.1% adjusted accuracy (27.6% improvement) for classifying audio recording environment.

A set of spectrograms designed to teach about common features of sound events (duration, intensity, pitch, timbre, pattern, speed). The digital files are provided so that anyone can 3D print these models for their own lessons or projects.