In this paper we present a novel method for jointly extracting beats and downbeats from
audio signals. A recurrent neural network operating directly on magnitude spectrograms is …

In this paper, we undertake a critical assessment of a stateof-the-art deep neural network
approach for computational rhythm analysis. Our methodology is to deconstruct this …

As an important format of multimedia, music has filled almost everyone's life. Automatic
analyzing of music is a significant step to satisfy people's need for music retrieval and music …

In this paper we present a new beat tracking algorithm which extends an existing state-of-the-
art system with a multi-model approach to represent different music styles. The system uses …

Existing systems for automatic transcription of drum tracks from polyphonic music focus on
detecting drum instrument onsets but lack consideration of additional meta information like …

Rhythmic patterns are an important structural element in music. This paper investigates the
use of rhythmic pattern modeling to infer metrical structure in musical audio recordings. We …

We present an automatic piano transcription system that converts polyphonic audio
recordings into musical scores. This has been a long-standing problem of music information …

The online estimation of rhythmic information, such as beat positions, downbeat positions,
and meter, is critical for many real-time music applications. Musical rhythm comprises …

In this paper, we propose a system that extracts the downbeat times from a beat-
synchronous audio feature stream of a music piece. Two recurrent neural networks are used …

A server system 500 is provided for receiving video clips having an associated
audio/musical track for processing at the server system. The system comprises a beat …