Meinard Müller

Meinard Müller
Friedrich-Alexander-University Erlangen-Nürnberg · International Audio Laboratories Erlangen

Professor
IEEE Fellow for contributions to Music Signal Processing

About

349
Publications
153,998
Reads
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9,089
Citations
Introduction
Meinard Müller studied mathematics and computer science at Bonn University, Germany. Since September 2012, he holds a professorship at the International Audio Laboratories Erlangen, a joint institution of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Fraunhofer IIS. His current research interests include music processing, audio signal processing, and music information retrieval. He is author of the textbook "Fundamentals of Music Processing" (www.music-processing.de).
Additional affiliations
March 2012 - August 2012
University of Bonn
Position
  • Professor (W2)
Description
  • Praktische Informatik/Audiosignalverarbeitung
December 2007 - February 2012
Universität des Saarlandes
Position
  • Senior Researcher
Description
  • Member of the the Cluster of Excellence, Multimodal Computing and Interaction (MMCI), MPI Informatik and Saarland University, Saarbrücken, Germany
September 2007 - February 2012
Max Planck Institute for Informatics
Position
  • Senior Researcher
Education
October 1990 - February 1997
University of Bonn
Field of study
  • Mathematics

Publications

Publications (349)
Preprint
Full-text available
In this study we examine the tonal organization of the 2016 GVM dataset, a newly-created corpus of high-quality multimedia field recordings of traditional Georgian singing (with focus on Svaneti) which we collected during the summer of 2016. Because of the peculiarities of the performance practice of traditional Svan singing (e.g, exhibiting a cons...
Preprint
Full-text available
This paper is concerned with how singers of Georgian traditional vocal music interact when singing together. Applying a variety of computational methods from audio signal processing and music information retrieval (MIR), we examine three existing corpora of (field) recordings for manifestations of a high degree of mutual coordination of the singers...
Presentation
Full-text available
This presentation is concerned with how singers of Georgian traditional vocal music interact when singing together. Applying a variety of computational methods from audio signal processing and music information retrieval (MIR), we examine three existing corpora of (field) recordings for manifestations of a high degree of mutual coordination of the...
Article
Three-voiced funeral songs from Svaneti in North-West Georgia (also referred to as Zär) are believed to represent one of Georgia’s oldest preserved forms of collective music-making. Throughout a Zär performance, the singers often jointly and intentionally drift upwards in pitch. Furthermore, the singers tend to use pitch slides at the beginning and...
Article
Full-text available
Existing acoustic scene classification (ASC) systems often fail to generalize across different recording devices. In this work, we present an unsupervised domain adaptation method for ASC based on data standardization and feature projection. First, log-amplitude spectro-temporal features are standardized in a band-wise fashion over samples and time...
Preprint
Full-text available
Attention-based Transformer models have been increasingly employed for automatic music generation. To condition the generation process of such a model with a user-specified sequence, a popular approach is to take that conditioning sequence as a priming sequence and ask a Transformer decoder to generate a continuation. However, this prompt-based con...
Article
Full-text available
This paper approaches the automatic detection of musical patterns in audio recordings with a particular focus on leitmotifs, which are specific types of patterns associated with certain characters, places, items, or feelings occurring in an opera or movie soundtrack. The detection of such leitmotifs is particularly challenging since their appearanc...
Preprint
Full-text available
The deployment of machine listening algorithms in real-life applications is often impeded by a domain shift caused for instance by different microphone characteristics. In this paper, we propose a novel domain adaptation strategy based on disentanglement learning. The goal is to disentangle task-specific and domain-specific characteristics in the a...
Article
Full-text available
This paper deals with a scoreaudio music retrieval task where the aim is to find relevant audio recordings of Western classical music, given a short monophonic musical theme in symbolic notation as a query. Strategies for comparing score and audio data are often based on a common mid-level representation, such as chroma features, which capture melo...
Preprint
Full-text available
In this article, we show how music may serve as a vehicle to support education in signal processing. Using Fourier analysis as a concrete example, we show how the music domain provides motivating and tangible applications that make learning signal processing an interactive pursuit. Furthermore, we indicate how software tools, originally developed f...
Article
Full-text available
Automatically detecting the presence of singing in music audio recordings is a central task within music information retrieval. While modern machine-learning systems produce high-quality results on this task, the reported experiments are usually limited to popular music and the trained systems often overfit to confounding factors. In this paper, we...
Article
Full-text available
Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In this scenario, a fast response from the system is...
Article
Full-text available
In this artaicle, we illustrate how music may serve as a vehicle to support education in signal processing. Using Fourier analysis as a concrete example, we demonstrate how the music domain provides motivating and tangible applications that make learning signal processing an interactive pursuit. Furthermore, we indicate how software tools, original...
Article
This article presents a multimodal dataset comprising various representations and annotations of Franz Schubert’s song cycle Winterreise . Schubert’s seminal work constitutes an outstanding example of the Romantic song cycle—a central genre within Western classical music. Our dataset unifies several public sources and annotations carefully created...
Article
Full-text available
This paper provides a guide through the FMP notebooks, a comprehensive collection of educational material for teaching and learning fundamentals of music processing (FMP) with a particular focus on the audio domain. Organized in nine parts that consist of more than 100 individual notebooks, this collection discusses well-established topics in music...
Chapter
Audio signals are typically complex mixtures of different sound sources. The sound sources can be several people talking simultaneously in a room, different instruments playing together, or a speaker talking in the foreground with music being played in the background.
Chapter
One of the attributes distinguishing music from random sound sources is the hierarchical structure in which music is organized. At the lowest level, one has events such as individual notes, which are characterized by the way they sound, their timbre, pitch, and duration.
Chapter
Music can be represented in many different ways and formats. For example, a composer may write down a composition in the form of a musical score. In a score, musical symbols are used to visually encode notes and how these notes are to be played by a musician.
Chapter
In music, harmony refers to the simultaneous sound of different notes that form a cohesive entity in the mind of the listener. The main constituent components of harmony, at least in the Western music tradition, are chords, which are musical constructs that typically consist of three or more notes.
Chapter
Temporal and structural regularities are perhaps the most important incentives for people to get involved and to interact with music. It is the beat that drives music forward and provides the temporal framework of a piece of music.
Chapter
Music can be described and represented in many different ways including sheet music, symbolic representations, and audio recordings. For each of these representations, there may exist different versions that correspond to the same musical work.
Chapter
The revolution in music distribution and storage brought about by digital technology has fueled tremendous interest in and attention to the ways that information technology can be applied to this kind of content. The rapidly growing corpus of digitally available music data requires novel technologies that allow users to browse personal collections...
Chapter
As we have seen in the last chapter, music signals are generally complex sound mixtures that consist of a multitude of different sound components. Because of this complexity, the extraction of musically relevant information from a waveform constitutes a difficult problem.
Chapter
The goal of automatic music segmentation is to calculate boundaries between musical parts or sections that are perceived as semantic entities. Such sections are often characterized by specific musical properties such as instrumentation, dynamics, tempo, or rhythm. Recent data-driven approaches often phrase music segmentation as a binary classificat...
Article
Full-text available
In this paper, we adapt a recently proposed U-net deep neural network architecture from melody to bass transcription. We investigate pitch shifting and random equalization as data augmentation techniques. In a parameter importance study, we study the influence of the skip connection strategy between the encoder and decoder layers, the data augmenta...
Preprint
Full-text available
The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop ‘Music, Computing, and Health’ was held to discuss best practices and state-of-the-art at the inters...
Book
The textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval (MIR). Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, signal processing, computer science,...
Article
Full-text available
The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the inters...
Article
Full-text available
While Georgia has a long history of orally transmitted polyphonic singing, there is still an ongoing controversial discussion among ethnomusicologists on the tuning system underlying this type of music. First attempts have been made to analyze tonal properties (e. g., harmonic and melodic intervals) based on fundamental frequency (F0) trajectories....
Book
Full-text available
In this study we examine the tonal organization of a series of recordings of liturgical chants, sung in 1966 by the Georgian master singer Artem Erkomaishvili. This dataset is the oldest corpus of Georgian chants from which the time synchronous F0-trajectories for all three voices have been reliably determined (Müller et al. 2017). It is therefore...
Article
While global key and chord estimation for both popular and classical music recordings have received a lot of attention, little research has been devoted to estimating the local key for classical music. Partly, this may be due to its inherent ambiguity and subjectivity, which makes annotating local keys a challenging task. In this article, we approa...
Conference Paper
Full-text available
Even though local tempo estimation promises musicological insights into expressive musical performances, it has never received as much attention in the music information retrieval (MIR) research community as either beat tracking or global tempo estimation. One reason for this may be the lack of a generally accepted definition. In this paper, we dis...
Conference Paper
Full-text available
From the 19th century on, several composers of Western opera made use of leitmotifs (short musical ideas referring to semantic entities such as characters, places, items, or feelings) for guiding the audience through the plot and illustrating the events on stage. A prime example of this compositional technique is Richard Wagner's four-opera cycle D...
Conference Paper
Full-text available
The computational analysis of music has traditionally seen a sharp divide between the "audio approach" relying on signal processing and the "symbolic approach" based on scores. Likewise, there has also been an unfortunate gap between any such computational endeavour and more traditional approaches as used in historical musicology. In this paper, we...
Article
Full-text available
With the advent of deep learning, global tempo estimation accuracy has reached a new peak, which presents a great opportunity to evaluate our evaluation practices. In this article, we discuss presumed and actual applications, the pros and cons of commonly used metrics, and the suitability of popular datasets. To guide future research, we present re...
Article
Full-text available
Choral singing is a central part of musical cultures across the world, yet many facets of this widespread form of polyphonic singing are still to be explored. Music information retrieval (MIR) research on choral singing benefits from multitrack recordings of the individual singing voices. However, there exist only few publicly available multitrack...
Preprint
In this paper we examine the tonal organization of a series of recordings of liturgical chants, sung in 1966 by the Georgian master singer Artem Erkomaishvili. The aim of the study is to understand the melodic and harmonic tuning systems used by this exceptional singer, a subject that has long been the topic of intense and highly controversial disc...
Preprint
Full-text available
The performance of machine learning algorithms is known to be negatively affected by possible mismatches between training (source) and test (target) data distributions. In fact, this problem emerges whenever an acoustic scene classification system which has been trained on data recorded by a given device is applied to samples acquired under differe...
Preprint
Full-text available
MIDI-sheet music alignment is the task of finding correspondences between a MIDI representation of a piece and its corresponding sheet music images. Rather than using optical music recognition to bridge the gap between sheet music and MIDI, we explore an alternative approach: projecting the MIDI data into pixel space and performing alignment in the...
Article
Full-text available
The analysis of recorded audio material using computational methods has received increased attention in ethnomusicological research. We present a curated dataset of traditional Georgian vocal music for computational musicology. The corpus is based on historic tape recordings of three-voice Georgian songs performed by the the former master chanter A...
Technical Report
Full-text available
In this contribution, we introduce various tools that are useful in the context of score following applications, where measures are highlighted synchronously to audio playback [1,3]. Such applications require alignments between sheet music and audio representations [2]. Often, such alignments can be computed automatically in the case that the sheet...
Chapter
In this paper, we approach the problem of detecting segments of singing voice activity in opera recordings. We consider three state-of-the-art methods for singing voice detection based on supervised deep learning. We train and test these models on a novel dataset comprising three annotated performances (versions) of Richard Wagner’s opera “Die Walk...
Article
Full-text available
Cross-version music retrieval aims at identifying all versions of a given piece of music using a short query audio fragment. One previous approach, which is particularly suited for Western classical music, is based on a nearest neighbor search using short sequences of chroma features, also referred to as audio shingles. From the viewpoint of effici...
Conference Paper
Full-text available
Western classical music comprises a rich repertoire composed for different ensembles. Often, these ensembles consist of instruments from one or two of the families wood-winds, brass, piano, vocals, and strings. In this paper, we consider the task of automatically recognizing instrument families from music recordings. As one main contribution , we i...
Conference Paper
Full-text available
Unaccompanied vocal music is a central part of Western art music, yet it requires excellent skills for singers to achieve proper intonation. In this paper, we analyze intonation deficiencies by introducing an intonation cost measure that can be computed from choir recordings and may help to assess the singers' intonation quality. With our approach...
Conference Paper
Full-text available
In this paper, we introduce a novel collection of educational material for teaching and learning fundamentals of music processing (FMP) with a particular focus on the audio domain. This collection, referred to as FMP notebooks , discusses well-established topics in Music Information Retrieval (MIR) as motivating application scenarios. The FMP noteb...
Conference Paper
Full-text available
Traditional multipart-singing is an essential component of the national identity of Georgia. It has been an active field of ethnomusicological research since more than 100 years, with a whole series of thematically very diverse research questions. Here, we report on the generation of a new research corpus of traditional Georgian vocal music collect...
Preprint
Full-text available
In this article we explore how the different semantics of spectrograms' time and frequency axes can be exploited for musical tempo and key estimation using Convolutional Neural Networks (CNN). By addressing both tasks with the same network architectures ranging from shallow, domain-specific approaches to deep variants with directional filters, we s...
Article
Full-text available
There has been a rapid growth of digitally available music data, including audio recordings, digitized images of sheet music, album covers and liner notes, and video clips. This huge amount of data calls for retrieval strategies that allow users to explore large music collections in a convenient way. More precisely, there is a need for cross-modal...
Conference Paper
Full-text available
In this paper, we evaluate hand-crafted features as well as features learned from data using a convolutional neural network (CNN) for different fundamental frequency classification tasks. We compare classification based on full (variable-length) contours and classification based on fixed-sized subcontours in combination with a fusion strategy. Our...