Music information retrieval (MIR) is an emerging research area that receives growing
attention from both the research community and music industry. It addresses the problem of …

Scientists and researchers have tried to establish a bond between the emotions conveyed
and the subsequent mood perceived in a person. Emotions play a major role in terms of our …

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic
data, and other modalities. While reviews have been written of some of this work before, no …

A huge increase in the number of digital music tracks has created the necessity to develop
an automated tool to extract the useful information from these tracks. As this information has …

This book provides a comprehensive overview of music data analysis, from introductory
material to advanced concepts. It covers various applications including transcription and …

Research on the music-language interface has extensively investigated similarities and
differences of poetic and musical meter, but largely disregarded melody. Using a measure of …

Song sentiment analysis attracts much attention in research areas such as acoustic signal
processing (ASP) and natural language processing (NLP). The text-based efforts in the NLP …

A central problem in music information retrieval is audio-based music classification. Current
music classification systems follow a frame-based analysis model. A whole song is split into …

The increasing use of digital media in daily life has resulted in a need for novel multimedia
data analysis techniques. Case-based Reasoning (CBR) solves problems using the already …

To classify time series by nearest neighbors, we need to specify or learn one or several
distance measures. We consider variations of the Mahalanobis distance measures which …