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 …

We introduce the Free Music Archive (FMA), an open and easily accessible dataset suitable
for evaluating several tasks in MIR, a field concerned with browsing, searching, and …

An Introduction to Audio Content Analysis Enables readers to understand the algorithmic
analysis of musical audio signals with AI-driven approaches An Introduction to Audio …

In this paper various supervised machine learning techniques were applied to classify cattle
behaviour patterns recorded using collar systems with 3-axis accelerometer and …

Many tasks in music information retrieval, such as recommendation, and playlist generation
for online radio, fall naturally into the query-by-example setting, wherein a user queries the …

One of the goals of the music information retrieval (MIR) community is to research new
methods and create new systems that can efficiently and effectively retrieve and recommend …

Our goal is to automatically identify which species of bird is present in an audio recording
using supervised learning. Devising effective algorithms for bird species classification is a …

The rapid increase in the amount of on-line music services creates a need for automatic
extraction of information from songs, music indexing and recommendation. But Music …

In this paper we present a novel approach to computing music similarity based on block-
level features. We first introduce three novel block-level features—the Variance Delta …

This paper discusses the concept of transfer learning and its potential applications to MIR
tasks such as music audio classification and similarity. In a traditional supervised machine …