The main objectives of the internship will be: 1. to develop a graphical interface to train vocalization annotation models, to visualize their performance and to re-annotate parts of the dataset accordingly (in a similar fashion as semi-supervised learning); 2. to develop the corresponding software backend: data management (audio and annotations), serving and local persistence of the models (MLOps); 3. to collaborate with the project members to define the needs, establish the specifications or integrate pre-existing tools. This objective also implies collaborating with international researchers, and making an open source tool available to the public. The development will be incremental: a first prototype will allow to train models and to present their evaluation on the interface. A second prototype will offer advanced editing possibilities of the dataset (re-annotation of parts of the audio according to the results of the model), and the final version will integrate advanced analysis tools (dataset errors detection, spectrograms dimensionality reduction for visualization and/or clustering, syntactic analysis of song sequences, ...)

Portable biosensors become more popular every year. In this context, I propose NeuriGUI, a modular and cross-platform graphical interface that connects to those biosensors for real-time processing, exploring and storing of electrophysiological signals. The NeuriGUI acts as a common entry point in brain-computer interfaces, making it possible to plug in downstream third-party applications for real-time analysis of the incoming signal. NeuriGUI is 100% free and open source.