Understanding the interplay between speech and gesture is crucial for linguistic and cognitive research. The current prototype, available on GitHub, aims to automate the analysis of temporal alignment between spoken demonstrative pronouns and pointing gestures in video recordings. By integrating computer vision (via Google’s MediaPipe) and speech recognition (using language-specific Vosk models) using Python, the workflow provides enriched video annotations and alignment data, offering valuable insights into deictic communication.