Tejaswinee

Dr Tejaswinee Kelkar


Researcher in Music Technology, Data Scientist


contact: tejaswinee.kelkar[at]gmail.com



Teaching


Motion Capture

The course aims to provide knowledge and skills in recording, visualising, and analysing human body motion. This includes learning about human anatomy and biomechanics and getting hands-on experience with setting up, calibrating, tracking, and recording with different types of motion capture systems. This course is taught every spring and is a part of the Music, Communication and Technology program at Institute of musicology, University of Oslo.

Research Methods

The aim of the course is to develop knowledge of and skills in various research methods, tools and issues in the field of music, communication and technology. These range from qualitative to quantitative methods, and with perspectives spanning from the arts and humanities to the social and natural sciences. The course will prepare the student for carrying out research and development in the field. In this course, I cover a broad array of topics from the philosophy of science, to artistic research, to statistical methods. This course is taught every fall and is a part of the Music, Communication and Technology program at Institute of musicology, University of Oslo.

Little Bits Synth Workshop

WoNoMute og teknologisatsingen for kvinner ved IMV ønsker velkommen til introduksjonskurs i littleBits. littleBits er et sett med små komponenter som med magneter kan settes sammen i små, morsomme kretser. Med littleBits kan man lage ulike lyder, samtidig som man lærer grunnleggende oppbygning av analoge synther. I workshopen vil vi jobbe med å bygge morsomme lyder fra de ulike komponentene og deltagerne vil få små oppgaver og utfordringer. Hver deltager vil ha sin egen littleBits å jobbe med i workshopen. For å delta trengs ingen bakgrunnskunnskaper.

Girls Music Tech Camp

This fall, I got the opportunity to teach a week long music technology camp during week 40, which is usually the week of Høstferie or fall break. Schools do not teach this week, and students were therefore, able to attend this camp. We decided to include the following tools in the camp: - Day 1: littleBits - Day 2: Gibber.cc - Day 3: Audacity - Day 4: Sonic Visualizer - Day 5: Project Demonstrations In addition to this, we had the following activities in the camp: - Recording sounds in the wild - A visit to the anechoic chamber in the Physics Department at UiO

Music and Machine Learning

This day-long course was held at Research Bazaar, teaching music processing and machine learning in jupyter using librosa and creating an audio category classifier based on scikit-learn. This workshop will teach how to handle sound files in python, compute sound and audio features from them, and run machine learning algorithms on them. This could be for anyone looking for supervised and unsupervised learning from sound files, using techniques for classification of sounds into one or more classes, and clustering of sounds based on extracted features. It will use Python 3 and some state of the art libraries in the field: Librosa, Pandas, and Scikit-Learn, all of which are open software, enabling people to be able to use their knowledge after the workshop. Here is the course material for the intensive day-long seminar on music and machine learning conducted in research bazaar.

Gibber and LiveCoding

Tejaswinee Kelkar holder en workshop i live-coding, med utgangspunkt i Gibber, som er en digital gratis plattform for audiovisuell musikkfremføring og komposisjon. Gibber inneholder blant annet funksjoner for lydsyntese, musikalske sekvenser, 2D-tegning, 3D-konstruksjon- og manipulering. På slutten av denne workshopen vil du lett kunne lage musikalske kodestykker og endre dem i sanntid. Workshopen passer for nybegynnere og er praktisk rettet. Ta med egen laptop og hodetelefoner. Sjekk gjerne ut Gibber på forhånd på https://gibber.cc/


Last updated-> May 2022