We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:

 

 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 

 

 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis

UbicaLab

Wireless Networking

Educational Technologies

GitHub

 

 

Back Dzhambazov G, Miron M, Serra X. Lyrics to audio alignment in polyphonic audio. Music Information Retrieval Evaluation eXchange (MIREX 2017)

Dzhambazov G, Miron M, Serra X. Lyrics to audio alignment in polyphonic audio. Music Information Retrieval Evaluation eXchange (MIREX 2017)

In this paper we describe the two algorithms we submitted for the MIREX 2017 task of Automatic Lyrics-to-Audio Alignment. The task has as a goal the automatic detection of word boundaries in multi-instrumental English pop music. We rely on a phonetic recognizer based on hidden Markov models (HMM): a widely-used method for tracking phonemes in speech processing problems. Tracking lyrics in music audio is harder than tracking text in speech because, unlike speech, the singing voice is mixed with multiple instruments. To address this obstacle we propose the application of two separate methods for segregating the singing voice from the multi-instrumental mix. One of them is based on the detection of vocal harmonic partials, whereas the other extracts the vocal content by means of source separation.

Additional material: