🤖 AI Summary
Existing speech analysis tools struggle to integrate with deep learning representations and lack support for interactive, multidimensional comparison of speech features. To address these limitations, this work proposes an interactive, client-server speech visualization platform. The backend, implemented in Python, handles continuous, discrete, and variable-length speech representations, while the frontend provides a web-based interface enabling synchronized audio playback, TextGrid annotation, and forced alignment. The system further supports configurable distance metrics and alignment strategies. This platform represents the first seamless integration of deep learning–derived speech representations with interactive visualization, substantially enhancing the efficiency and intuitiveness of speech analysis, representation validation, and pronunciation training.
📝 Abstract
This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can be cumbersome to integrate them with modern deep learning representations and use them for comparison. Speech Playground addresses this by combining a Python backend with a web-based frontend for interactive exploration of multiple feature types, including continuous, discrete, and variable-length representations. It includes TextGrid and forced alignment support together with configurable distance and alignment settings for visual and auditory comparison. Speech Playground is intended for use in speech research, representation validation, and computer-aided pronunciation training (CAPT)-oriented experimentation.