In this paper, we describe an efficient method for audio matching which performs effectively for a wide range of classical music. The basic goal of audio matching can be describe...
We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Low level audio features are extracted from the raw audio data on sh...
We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting bo...
The singing voice is the oldest and most complex musical instrument. A familiar singer’s voice is easily recognizable for humans, even when hearing a song for the first time. O...
A pitch spelling algorithm predicts the pitch names of the notes in a musical passage when given the onset-time, MIDI note number and possibly the duration and voice of each note....
The use of HMM (Hidden Markov Models) for speech recognition has been successful for various applications in the past decades. However, the use of continuous HMM (CHMM) for melody...
In music genre classification the decision time is typically of the order of several seconds, however, most automatic music genre classification systems focus on short time feat...
Though music is fundamentally an aural phenomenon, we often communicate about music through visual means. The paper examines a number of visualization techniques developed for mus...
In this paper we present a system for the automatic mining of information from music reviews. We demonstrate a system which has the ability to automatically classify reviews accor...
Xiao Hu, J. Stephen Downie, Kris West, Andreas F. ...
This paper presents ACE (Autonomous Classification Engine), a framework for using and optimizing classifiers. Given a set of feature vectors, ACE experiments with a variety of cla...
Cory McKay, Rebecca Fiebrink, Daniel McEnnis, Bein...