@ARTICLE{Szymański_Filip_Timbra:_2024,
 author={Szymański, Filip and Łukasik, Ewa and Chudy, Magdalena},
 volume={vol. 70},
 number={No 2},
 journal={International Journal of Electronics and Telecommunications},
 pages={349-354},
 howpublished={online},
 year={2024},
 publisher={Polish Academy of Sciences Committee of Electronics and Telecommunications},
 abstract={Dariah.lab is a research infrastructure created for digital humanities, consisting of state-of-the-art hardware and dedicated software tools. One of the tools developed for digital musicology is Timbra, a web-based application for conducting research on sound timbre. The aim was to create an easy-touse online tool for non-programmers. The tool can be used to calculate, visualise, and compare different timbre characteristics of uploaded audio files and to export the extracted parameters in CSV format for further processing, e.g. by classification tools. The application offers extraction and visualisation of scalar features such as zero crossing rate, fundamental frequency, spectral centroid, spectral roll-off, spectral flatness, band energy ratio, as well as feature vectors (e.g. chromagram, spectral contrast, spectrogram, and MFCCs). An interested user can compare selected sound characteristics using various types of plots and run dissimilarity analysis of timbre parameters by means of 2D or 3D multidimensional scaling (MDS). The paper showcases potential applications of the tool based on presented case studies. In terms of implementation, the calculations are performed at the backend Django server using Librosa and standard Python libraries. Dash library is used for the frontend. By offering an easy-to-use tool accessible anytime and anywhere through the Internet, we want to facilitate timbre analysis for a broader group of researchers, e.g. sound engineers, luthiers, phoneticians, or musicologists.},
 type={Article},
 title={Timbra: An online tool for feature extraction, comparative analysis and visualization of timbre},
 URL={http://ochroma.man.poznan.pl/Content/131792/11_4597_Szymanski_sk.pdf},
 doi={10.24425/ijet.2024.149551},
 keywords={timbre, audio descriptors, feature extraction, comparative analysis, visualization},
}