SPLt

SPLt is a compact, open-source software library designed for processing and analyzing speech signals. Developed to facilitate research in speech engineering and related fields, SPLt provides a comprehensive suite of tools for tasks such as speech signal filtering, feature extraction, and classification. The library emphasizes modularity and extensibility, making it suitable for both academic research and application development.

The core functionalities of SPLt include digital filtering, spectral analysis, pitch detection, and formant estimation. It supports multiple audio formats and can handle large datasets efficiently. SPLt is implemented primarily in Python, leveraging widely used scientific computing libraries such as NumPy and SciPy, which enables easy integration with other data analysis pipelines.

SPLt also offers visualization features for examining speech signals and their properties, which aids in interpretability and diagnostic evaluations. Its open-source license encourages community contributions, with ongoing updates and improvements managed via a public repository.

Designed for accessibility, SPLt is suitable for users with varying levels of experience in signal processing. Its documentation includes tutorials, example scripts, and comprehensive API references to facilitate learning and implementation.

Overall, SPLt aims to support researchers and developers in advancing speech processing technologies by providing a flexible and efficient toolkit adaptable to diverse experimental needs and real-world applications.