instrEmma

instrEmma is a research project and open-source software suite focused on the automated analysis of musical performances. Developed by a team of researchers, instrEmma aims to provide tools for extracting detailed performance characteristics from audio recordings of instrumental music. Its primary goal is to move beyond simple transcription and delve into nuanced aspects of how a piece is played, such as timing variations, dynamics, articulation, and even subtle aspects of timbre.

The software is designed to be flexible and adaptable to various musical instruments and genres. It utilizes a combination of signal processing techniques and machine learning algorithms to identify and quantify these performance attributes. Researchers can use instrEmma to study expressive performance practices, compare different interpretations of the same work, or investigate the relationship between performance and listener perception.

Key functionalities of instrEmma include the estimation of tempo and rhythmic deviations, the analysis of loudness variations, and the identification of note onsets and offsets with high precision. The project emphasizes making its tools accessible to the broader musicological and computational music research communities, encouraging further development and application of automated performance analysis. Documentation and tutorials are typically provided to guide users in applying the software to their specific research questions.