Open Source Softwares/Datasets

M3L is an open-source toolkit for multi-modal machine listening, providing infrastructure and recipes to build, train, and evaluate models that combine audio with other modalities.

SBSS is a Python-based, research-oriented toolkit for scalable blind source separation (BSS) that includes end-to-end components such as neural FCA and neural FastFCA.

Aiaccel is an open-source Python toolkit designed to accelerate machine learning research, especially on high-performance computing (HPC) clusters such as ABCI.

The LEAD dataset provides strong labels for sound events, in which each clip has 20 different annotations. It allows us to investigate how annotations vary among different annotators and develop SED models that are robust to the variations.

SaSLaW is a spontaneous dialogue speech corpus containing synchronous recordings of what speakers speak, listen to, and watch.