  psifx is a plug-and-play multi-modal feature extraction toolkit, aiming to
facilitate and democratize the use of state-of-the-art machine learning
techniques for human sciences research. It is motivated by a need (a) to
automate and standardize data annotation processes, otherwise involving
expensive, lengthy, and inconsistent human labor, such as the transcription or
coding of behavior changes from audio and video sources; (b) to develop and
distribute open-source community-driven psychology research software; and (c)
to enable large-scale access and ease of use to non-expert users. The framework
contains an array of tools for tasks, such as speaker diarization,
closed-caption transcription and translation from audio, as well as body, hand,
and facial pose estimation and gaze tracking from video. The package has been
designed with a modular and task-oriented approach, enabling the community to
add or update new tools easily. We strongly hope that this package will provide
psychologists a simple and practical solution for efficiently a range of audio,
linguistic, and visual features from audio and video, thereby creating new
opportunities for in-depth study of real-time behavioral phenomena.
