We consider the problem of personalized text-based music retrieval where users’ history of preferences are taken into account in addition to their issued textual queries. Current retrieval methods mostly rely on songs meta-data. This limits the query vocabulary. Moreover, it is very costly to gather this information in large collections of music. Alternatively, we use music annotations retrieve...

Background and Purpose: Due to adverse effects of cancer on children's mental health, relaxation, chemotherapy side-effects and positive effects of music therapy on stress, this study was performed with the goal to determine the effect of music therapy on children's stress after chemotherapy. Methods: The present study is a randomized clinical trial done on 32 children undergoing cancer chem...

30 second-snippets from 37 songs have been automatically extracted. All phonemes from this pieces have been manually labeled. The considered genre was popular music. 21 songs have been performed by male singers. 16 songs have been performed by female singers. Altogether 2244 phonemes have been manually labeled and can be used by the system. Only 15 voiced phonemes have been distinguished, becau...

Searching and organizing growing digital music collections requires automatic classification of music. Our system for artist and genre identification uses support vector machines to classify songs based on features calculated over their entire lengths. Since support vector machines are exemplar-based classifiers, training on and classifying entire songs instead of short-time features makes intu...

In this paper a humming method for music information retrieval is presented. The system uses a database with real songs and does not need another type of symbolic representation of them. The system employs an original fingerprint based on chroma vectors to characterize the humming and the references songs. With this fingerprint, it is possible to get the hummed songs without needed of transcrip...

Introduction Music genres allow the categorization of music into broad groups of related songs for use in applications such as song recommender systems based on genre. Many existing songs are unlabeled, and new songs are constantly being released. While hand-labeling them all would be too tedious, classifying them by genre can fit them into categories for use in recommendation. Also, even if th...

People have remarkably diverse tastes in music, which reflect diversity in personalities, cultures and age groups. Recently Yahoo! Music offers a wealth of information and services related to many aspects of music, such as user ratings, which can be utilized to analyze the encoded information on how songs are grouped, which artists complement each other, and which songs users would like to list...

The recognition of text and tune in songs was examined in a music-agnosic patient and five matched controls. Listeners had to focus on one component of the song at a time (text or music) and had to decide whether the component was familiar or unfamiliar. Songs were either matched (i.e., an original familiar or an original unfamiliar song) or mismatched (a combination of a familiar component wit...

This study explains the metrical hierarchical structure of music that deals with onsets of musical events and the distances between them. The metrical structure is essential for the temporal organization of notes and the perception of rhythm. The paper shows the suitability of inter onset interval histograms to cover major metrical characteristics such as dominant metrical levels, regularity an...