The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources

نویسندگان

  • Dmitry Bogdanov
  • Alastair Porter
  • Julián Urbano
  • Hendrik Schreiber
چکیده

This paper provides an overview of the AcousticBrainz Genre Task organized as part of theMediaEval 2017 Benchmarking Initiative for Multimedia Evaluation. The task is focused on content-based music genre recognition using genre annotations from multiple sources and large-scale music features data available in the AcousticBrainz database. The goal of our task is to explore how the same music pieces can be annotated differently by different communities following different genre taxonomies, and how this should be addressed by content-based genre recognition systems. We present the task challenges, the employed ground-truth information and datasets, and the evaluation methodology.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hierarchical Multilabel Classification and Voting for Genre Classification

This paper summarizes our contribution (team DBIS) to the AcousticBrainz Genre Task: Content-based music genre recognition from multiple sources as part of MediaEval 2017. We utilize a hierarchical set of multilabel classifiers to predict genres and subgenres and rely on a voting scheme to predict labels across datasets.

متن کامل

ICSI in MediaEval 2017 Multi-Genre Music Task

We present our approach and result for the MediaEval 2017 AcousticBrainz Content-based music genre recognition task. Experimental results show that the best results come from random forest with partial feature selection.

متن کامل

Single and Multi Column Neural Networks for Content-based Music Genre Recognition

This working note reports approaches of team KART to MediaEval2017 AcousticBrainz Genre Task and their results. To solve the problem, we mainly considered the sparsity and noise of data, network design for the multi-label classification, and implementation of successful Deep Neural Network (DNN) models. We propose three steps of preprocessing and depict two different approaches: a single-column...

متن کامل

MediaEval 2017 AcousticBrainz Genre Task: Multilayer Perceptron Approach

This report describes the approach developed by the JKU team for the MediaEval 2017 AcousticBrainz Genre Task. After experimenting with various classifiers on the development dataset, our final approach is based on multilayer perceptron classifiers.

متن کامل

DNN in the AcousticBrainz Genre Task 2017

This paper presents a method of genre classification using deep neural networks for the AcousticBrainz genre classification task of MediaEval 2017.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017