AVA: An Interactive System for Visual and Quantitative Analyses of Vibrato and Portamento Performance Styles.
Luwei Yang, Khalid Z. Rajab, Elaine Chew · Queen Mary Research Online (Queen Mary University of London) · 2016
Vibratos and portamenti are important expressive features for characterizing performance style on instruments capable of continuous pitch variation such as strings and voice.Accurate study of these features is impeded by time consuming manual annotations.We present AVA, an interactive tool for automated detection, analysis, and visualization of vibratos and portamenti.The system implements a Filter Diagonalization Method (FDM)-based and a Hidden Markov Model-based method for vibrato and portamento detection.Vibrato parameters are reported directly from the FDM, and portamento parameters are given by the best fit Logistic Model.The graphical user interface (GUI) allows the user to edit the detection results, to view each vibrato or portamento, and to read the output parameters.The entire set of results can also be written to a text file for further statistical analysis.Applications of AVA include music summarization, similarity assessment, music learning, and musicological analysis.We demonstrate AVA's utility by using it to analyze vibratos and portamenti in solo performances of two Beijing opera roles and two string instruments, erhu and violin.