An review of automatic drum transcription

In Western popular music, drums and percussion are an important means to emphasize and shape the rhythm, often defining the musical style. If computers were able to analyze the drum part in recorded music, it would enable a variety of rhythm-related music processing tasks. Especially the detection and classification of drum sound events by computational methods is considered to be an important and challenging research problem in the broader field of Music Information Retrieval. Over the last two decades, several authors have attempted to tackle this problem under the umbrella term Automatic Drum Transcription(ADT).This paper presents a comprehensive review of ADT research, including a thorough discussion of the task-specific challenges, categorization of existing techniques, and evaluation of several state-of-the-art systems. To provide more insights on the practice of ADT systems, we focus on two families of ADT techniques, namely methods based on Nonnegative Matrix Factorization and Recurrent Neural Networks. We explain the methods’ technical details and drum-specific variations and evaluate these approaches on publicly available datasets with a consistent experimental setup. Finally, the open issues and under-explored areas in ADT research are identified and discussed, providing future directions in this fiel

Break-informed audio decomposition for interactive redrumming

Redrumming or drum replacement is used to substitute or enhance the drum hits in a song with one-shot drum sounds obtained from an external collection or database. In an ideal setting, this is done on multitrack audio, where one or more tracks are dedicated exclusively to drums and percussion. However, most non-professional producers and DJs only have access to mono or stereo downmixes of the music they work with. Motivated by this scenario, as well as previous work on decomposition techniques for audio signals, we propose a step towards enabling full-fledged redrumming with mono downmixes

Towards cover group thumbnailing

In this paper we investigate whether we can extract the commonalities shared by a group of cover songs or versions of the same musical piece. As a main contribution, we introduce the concept of cover group thumbnail, which is the most representative, essential subsequence for an entire group of versions. Opposed to previous approaches, we jointly consider all versions of a given song to compute a single cover group template, which then shows a high degree of robustness against version-specific aspects. To compute such a template, we introduce a modification of a recent audio thumbnailing technique. To evaluate the reliability of our conceptual contribution, we consider the task of templatebased version identification, where we show comparable accuracies to existing systems. Copyright © 2013 ACM.This work was supported by the Cluster of Excellence on Multimodal Computing and Interaction at Saarland University, JAEDOC069/2010, FP7-ICT-2011-8-318770, and 2009-SGR-1434. The International Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander-Universitat Erlangen-Nurnberg (FAU) and Fraunhofer IISPeer Reviewe

Unsupervised music structure annotation by time series structure features and segment similarity

Automatically inferring the structural properties of raw multimedia documents is essential in today's digitized society. Given its hierarchical and multi-faceted organization, musical pieces represent a challenge for current computational systems. In this article, we present a novel approach to music structure annotation based on the combination of structure features with time series similarity. Structure features encapsulate both local and global properties of a time series, and allow us to detect boundaries between homogeneous, novel, or repeated segments. Time series similarity is used to identify equivalent segments, corresponding to musically meaningful parts. Extensive tests with a total of five benchmark music collections and seven different human annotations show that the proposed approach is robust to different ground truth choices and parameter settings. Moreover, we see that it outperforms previous approaches evaluated under the same framework. © 1999-2012 IEEE.Peer Reviewe

Break-informed audio decomposition for interactive redrumming

Redrumming or drum replacement is used to substitute or enhance the drum hits in a song with one-shot drum sounds obtained from an external collection or database. In an ideal setting, this is done on multitrack audio, where one or more tracks are dedicated exclusively to drums and percussion. However, most non-professional producers and DJs only have access to mono or stereo downmixes of the music they work with. Motivated by this scenario, as well as previous work on decomposition techniques for audio signals, we propose a step towards enabling full-fledged redrumming with mono downmixes