Animal sound : què se sent quan s’és una cabra?

Aquest projecte treballa sobre la possibilitat d'aplicar tècniques d'enregistrament binaural en animals, en concret, en una cabra domèstica. Mitjançant uns micròfons col·locats dins les seves orelles i una petita càmera de vídeo muntada sobre el seu cap, s'obté un material audiovisual que permet fer-se una idea aproximada de com és la seva percepció del món. En base a un estudi de cognició comparada, es pretén trobar maneres de transformar els enregistraments obtinguts per tal d'adaptar el marc psicoacústic humà al de l'animal. L'objectiu és que una persona pugui sentir com ho fa un animal, encara que sigui d'una manera aproximada. Els materials obtinguts al llarg dels enregistraments són el punt de partida per a la construcció de paisatges sonors i peces audiovisuals diverses. Així doncs, el treball s'inicia amb el disseny i construcció d'un micròfon binaural, continua amb enregistraments de camp en animals i acaba amb l'edició, el processat i la composició dels paisatges sonors finals.

Bowing the violin : a case study for auditory-motor pattern modelling in the context of music performance

This project addresses methodological and technological challenges in the development of multi-modal data acquisition and analysis methods for the representation of instrumental playing technique in music performance through auditory-motor patterning models. The case study is violin playing: a multi-modal database of violin performances has been constructed by recording different musicians while playing short exercises on different violins. The exercise set and recording protocol have been designed to sample the space defined by dynamics (from piano to forte) and tone (from sul tasto to sul ponticello), for each bow stroke type being played on each of the four strings (three different pitches per string) at two different tempi. The data, containing audio, video, and motion capture streams, has been processed and segmented to facilitate upcoming analyses. From the acquired motion data, the positions of the instrument string ends and the bow hair ribbon ends are tracked and processed to obtain a number of bowing descriptors suited for a detailed description and analysis of the bow motion patterns taking place during performance. Likewise, a number of sound perceptual attributes are computed from the audio streams. Besides the methodology and the implementation of a number of data acquisition tools, this project introduces preliminary results from analyzing bowing technique on a multi-modal violin performance database that is unique in its class. A further contribution of this project is the data itself, which will be made available to the scientific community through the repovizz platform.