Christian Dittmar

Friedrich-Alexander-University of Erlangen-Nürnberg | FAU · Department of Electrical, Electronic and Communication Engineering

With regard to the wider area of AI/LT platform interoperability, we concentrate on two core aspects: (1) cross-platform search and discovery of resources and services; (2) composition of cross-platform service workflows. We devise five different levels (of increasing complexity) of platform interoperability that we suggest to implement in a wider...

With regard to the wider area of AI/LT platform interoperability, we concentrate on two core aspects: (1) cross-platform search and discovery of resources and services; (2) composition of cross-platform service workflows. We devise five different levels (of increasing complexity) of platform interoperability that we suggest to implement in a wider...

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 computat...

Retrieving short monophonic queries in music recordings is a challenging research problem in Music Information Retrieval (MIR). In jazz music, given a solo transcription, one retrieval task is to find the corresponding (potentially polyphonic) recording in a music collection. Many conventional systems approach such retrieval tasks by first extracti...

Web services allow permanent access to music from all over the world. Especially in the case of web services with user-supplied content, e.g., YouTube™, the available metadata is often incomplete or erroneous. On the other hand, a vast amount of high-quality and musically relevant metadata has been annotated in research areas such as Music Informat...

The use of pitch-informed solo and accompaniment separation as a tool for the creation of practice content

DJs and producers of sample-based electronic dance music (EDM) use breakbeats as an essential building block and rhythmic foundation for their artistic work. The practice of reusing and resequencing sampled drum breaks critically influenced modern musical genres such as hip hop, drum’n’bass, and jungle. While EDM artists have primarily sourced drum...

A typical micro-rhythmic trait of jazz performances is their ‘swing feel.’ According to several studies, uneven eighth notes contribute decisively to this perceived quality. In this paper we analyze the swing ratio (beat-upbeat ratio) implied by the drummer on the ride cymbal. Extending previous work, we propose a new method for semi-automatic swin...

This work addresses the extraction of high-quality component signals from drum solo recordings (breakbeats) for music production and remixing purposes. Specifically, we employ audio source separation techniques to recover sound events from the drum sound mixture corresponding to the individual drum strokes. Our separation approach is based on an in...

Music source separation aims at decomposing music recordings into their constituent component signals. Many existing techniques are based on separating a time-frequency representation of the mixture signal by applying suitable modeling techniques in conjunction with generalized Wiener filtering. Recently, the term α-Wiener filtering was coined toge...

Electronic Music (EM) is a popular family of genres which has increasingly received attention as a research subject in the field of MIR. A fundamental structural unit in EM are loops—audio fragments whose length can span several seconds. The devices commonly used to produce EM, such as sequencers and digital audio workstations, impose a musical str...

In the field of Music Information Retrieval (MIR), the automated detection of the singing voice within a given music recording constitutes a challenging and important research problem. The goal of this task is to find those segments within a given recording where one or several singers are active. In this study, we investigate the performance of st...

We present a system for the automatic separation of solo instruments and music accompaniment in polyphonic music recordings. Our approach is based on a pitch detection front-end and a tone-based spectral estimation. We assess the plausibility of using sound separation technologies to create practice material in a music education context. To better...

In this paper, a method for separation of harmonic and percussive elements in music recordings is presented. The proposed method is based on a simple spectral peak detection step followed by a phase expectation analysis that discriminates between harmonic and percussive components. The proposed method was tested on a database of 10 audio tracks and...

In this paper we present an audio tampering detection method based on the analysis of discontinuities in the framing grid, caused either by manipulations within the same recording or across recordings even with codec changes. The approach extends state of the art methods for MP3 framing grid detection with respect to efficiency and robustness, and...

Electronic dance music can be characterised to a large extent by its rhythmic properties. Besides the tempo, the basic rhythmic patterns play a major role. In this work we present a system that uses these features to classify electronic music tracks into subgenres. From each song, a drum pattern of 4 bars length is extracted incorporating source se...

A device for providing a television sequence has a database interface, a search request receiver, a television sequence rendition module and an output interface. The database interface accesses at least one database, using a search request. The search request receiver is formed to control the database interface so as to acquire at least audio conte...

Instrument recognition is an important task in music information retrieval (MIR). Whereas the recognition of musical instruments in monophonic recordings has been studied widely, the polyphonic case still is far from being solved. A new approach towards feature-based instrument recognition is presented that makes use of redundancies in the harmonic...

In this paper we present an audio tampering detection method based on the combination of blind microphone analysis and phase analysis of stable tones, e.g., the electrical network frequency (ENF). The proposed algorithm uses phase analysis to detect segments that might have been tampered. Afterwards, the segments are further analyzed using a featur...

Over the past years, the detection of onset times of acoustic events has been investigated in various publications. However, to our knowledge, there is no research on event detection on a broader scale. In this paper, we introduce a method to automatically detect "big" events in music pieces in order to match them with events in videos. Furthermore...

In this paper, we present an improved approach for audio tampering detection and localization based on the Electrical Network Frequency (ENF) analysis, combining analysis of the ENF phase, and ENF temporal pattern matching: The proposed algorithm uses phase discontinuity checking to detect regions that might have been tampered, which are then match...

In this paper, we present a novel approach to real-time detection of the string number and fretboard position from polyphonic guitar recordings. Our goal is to assess, if a music student is correctly performing guitar exercises presented via music education software or a remote guitar teacher. We combine a state-of-the art approach for multi-pitch...

In this paper, we study the effect of prior information on the quality of informed source separation algorithms. We present results with our system for solo and accompaniment separation and contrast our findings with two other state-of-the art approaches. Results suggest current separation techniques limit performance when compared to extraction pr...

In this paper, we propose a novel approach for music similarity estimation. It combines temporal segmentation of music signals with source separation into so-called tone objects. We solely use the timbre-related audio features Mel-Frequency Cepstral Coefficients (MFCC) and Octave-based Spectral Contrast (OSC) to describe the extracted tone objects....

Our goal is to obtain improved perceptual quality for separated solo instruments and accompaniment in polyphonic music. The proposed approach uses a pitch detection algorithm in conjunction with a spectral filtering based source separation. The algorithm was designed to work with polyphonic signals regardless of the main instrument, type of accompa...

With music markets shifting, the use of music in video productions has become increasingly important. Our novel research project “SyncGlobal“ addresses this global music licensing opportunity. Our goal is to find the best acoustic or semantic matches to any video sequence from large-scale intercultural music catalogs with minimal human effort. One...

In this paper, we present a novel audio synthesis model that allows us to simulate bass guitar tones with 11 different playing techniques to choose from. In contrast, previous approaches focussing on bass guitar synthesis only implemented the two slap techniques. We apply a digital waveguide model extended by different modular parts to imitate the...

This paper presents a toolbox that has been developed in order to facilitate the inspection of suspected music plagiarism cases. The basic concept is the use of techniques from Music Information Retrieval for semi-automatic inspection of original and suspect song. Basic types of music plagiarism are discussed. Several signal processing approaches s...

This paper addresses the use of Music Information Retrieval (MIR) techniques in music education and their integration in learning software. A general overview of systems that are either commer-cially available or in research stage is presented. Furthermore, three well-known MIR methods used in music learning systems and their state-of-the-art are d...

During the last year, many research efforts have been directed to the reffnement of sound source separation algorithms. However, little or no effort has been made to assess the impact of different spectral parameters as phase, magnitude and location of harmonic components in the resulting quality of the extracted signals. Recent developments in obj...

In this paper, we present the results of a pre-study on music performance analysis of ensemble music. Our aim is to implement a music classification system for the description of live recordings, for instance to help musicologist and musicians to analyze improvised ensemble performances. The main problem we deal with is the extraction of a suitable...

n this paper, we propose a novel method to parametrize and classify different frequency modulation techniques in bass guitar recordings. A parametric spectral estimation technique is applied to refine the fundamental frequency estimates derived from an existing bass transcription algorithm. We apply a two-stage taxonomy of bass playing styles with...

Songs2See is a music game developed based on pitch de-tection, sound separation, music transcription, interface de-velopment and audio analysis technologies.While keeping the entertainment and excitement of normal video games, Songs2See provides the users with a practice tool that makes the process of learning to play a musical instrument, a more e...

Pitch detection algorithms ffnd use in many different applications ranging from automatic music transcription, music classiffcation and analysis to sound separation. Most recently, music games and karaoke applications have also incorporated pitch detection algorithms in their gameplay. Music and audio games pose different technical requirements in...

Interactive software applications have proved to be powerful means for music education as they provide the user with real time performance assessment, unlimited orientation and prac-tice time, variable set of user selected features, entertaining ways of displaying content and variable levels of difficulty in a single application. The algorithms beh...

At the Fraunhofer Institute for Digital Media Technology (IDMT) in Ilmenau, Germany, two current research projects are directed towards core problems of Music Information Retrieval. The Songs2See project is supported by the Thuringian Ministry of Economy, Employment and Technology through granting funds of the European Fund for Regional Development...

This paper presents a novel method to detect and distinguish ten frequently used audio effects in recordings of electric guitar and bass. It is based on spectral analysis of audio segments located in the sustain part of previously detected guitar tones. Overall, 541 spectral, cepstral and harmonic features are extracted from short time spectra of t...

Large-scale systems for automatic content-based music recommendation require efficient computation of signal descriptors that are robust and relevant with regard to human perception in order to process extensive music archives. In this publication, a set of mid-level audio features suitable for efficient characterization of musical signals with reg...

This paper describes a feature-based approach for the note-wise classification of instruments in a polyphonic music segment. To reduce the amount of potential misclassification due to spectral overlapping of different instruments, we perform a pre-selection of notes. In doing so, we allow at most two instrument notes to overlap at the same time. If...

The characteristics of vocal segments in music are an important cue for automatic, content-based music recommendation, especially in the urban genre. In this paper, we investigate the classification of audio segments into singing and rap, using low-level acoustic features and a Bayesian classifier. GMMs are used as parametric clustering method to d...

In the majority of musical genres, music is basically composed of repetitive rhythmic structures (patterns). Especially in Latin American music, particular styles can be distinguished through characteristics of these patterns. Therefore, the aim of the present work is the automatic classification of musical genres from Latin America using automatic...

Automatic estimation of music mood has emerged as an important task in Music Information Retrieval. It has direct applications in music search engines and cross-modal multimedia tools. During the last years, Gaussian Mixture Models (GMM) became one of the most popular classifiers for mood estimation. One of the remaining key challenges is the impos...

Solving the task of phoneme recognition in music sound files may help for several practical applications: it enables lyrics transcription and as a consequence could provide further relevant information for the task of an automatic song classification. Beyond it can be used for lyrics alignment e.g. in karaoke applications. The effect of both differ...

In this paper, we present a rule-based classification framework that allows to describe musical genres by means of different musical properties. We compare the presented approach with a state-of-the-art genre classification system including feature extraction as well as different feature selection and feature space transformation methods. A set of...

Popular music video games are mostly examples of the rhythm game genre. They rarely respect the creative component of actually playing music. In this publication, a novel improvisation game-play element is introduced to account for the creativity. An evaluation is conducted to assess, whether improvising music as a game-play element in music games...

This paper describes a technical solution for automated slideshow generation by extracting a set of high-level features from music, such as beat grid, mood and genre and intelligently combining this set with image high-level features, such as mood, daytime- and scene classification. An advantage of this high-level concept is to enable the user to i...

In the last ten years, our ways to listen to music have drastically changed: In earlier times, we went to record stores or had to use low bit-rate audio coding to get some music and to store it on PCs. Nowadays, millions of songs are within reach via on-line distributors. Some music lovers already got terabytes of music on their hard disc. Users ar...

In this publication we describe a novel two-dimensional approach for automatic music genre classification. Although the subject poses a well studied task in Music Information Retrieval, some fundamental issues of genre classification have not been covered so far. Especially many modern genres are influenced by manifold musical styles. Most of all,...

Rhythmic descriptors are often utilized for semantic mu- sic classification, such as genre recognition or tempo de- tection. Several algorithms dealing with the extraction of rhythmic information from music signals were proposed in literature. Most of them derive a so-called beat histogram by auto-correlating a representation of the temporal enve-...

Considering its mediation role between the poles of rhythm, harmony, and melody, the bass plays a crucial role in most music genres. This paper introduces a novel set of transcription-based high-level features that characteri ze the bass and its interaction with other participating instrume nts. Furthermore, a new method to model and automatically...

Locating singing voice segments is essential for convenient index- ing, browsing and retrieval large music archives and catalogues. Furthermore, it is beneficial for automatic music transcription and annotations. TheapproachdescribedinthispaperusesMel-Frequency Cepstral Coefficients in conjunction with Gaussian Mixture Mod- els for discriminating t...

Automatic deriving of similarity relations between music pieces is an inherent field of music information retrieval research. Due to the nearly unrestricted amount of musical data, the real-world similarity search algorithms have to be highly efficient and scalable. The possible solution is to represent each music excerpt with a statistical model (...

Automatic lyrics synchronization for karaoke applications is a major challenge in the field of music information re- trieval. An important pre-requisite in order to precisely synchronize the music and corresponding text is the de- tection of single phonemes in the vocal part of polyphonic music. This paper describes a system, which detects the phon...

This publication introduces a software toolbox that encapsulates different algorithmic solutions directed towards the automatic extraction of symbolic note information from digitized music excerpts. This process, often referred to as automatic musictranscription is still confronted with many issues such as mimicking the human perception or making a...

Due to the growing amount of digital audio an increasing need to automatically categorize music and to create self-controlled and suitable playlists has been emerged. A few approaches to this task relying on low-level features have been published so far. Unfortunately the results utilizing those technologies are not sufficient yet. This paper gives...

A number of metadata standards have been published in recent years due to the increasing availability of multimedia content and the resulting issue of sorting and retrieving this content. One of the most recent efforts for a well defined metadata description is the ISO/IEC MPEG-7 standard, which takes a very broad approach towards the definition of...

The analysis and separation of audio signals into their original components is an important prerequisite to automatic transcription of music, extraction of metadata from audio data, and speaker separation in video conferencing. In this paper, a method for the separation of drum tracks from polyphonic music is proposed. It consists of an Independent...

This publication presents a method for the automatic detection and classification of three distinct drum in-struments in real world musical signals. The regarded instruments are kick, snare and hi-hat as agreed by the participants of the contest category Audio Drum Detec-tion within the 2nd Annual Music Information Retrieval Evaluation eXchange (MI...

Separation of instrument sounds from polyphonic music record-ings is a desirable signal processing functionality with a wide variety of applications in music production, music video games and music information retrieval. In general, sound source separa-tion algorithms attempt to exploit those characteristics of audio signals that differentiate one...

One of the most successful interactive TV applications are the mobile messaging TV services e.g. SMS chats. Within this paper we present novel approaches for enrichment of mobile messaging services utilizing content-based and col- laborative ltering methods. We depict the current work of a content and playout server used for integrating interactive...

This publication addresses the generation of a musical score of percussive un-pitched instruments. A musical event is defined as the occurrence of a sound of a musical instrument. The presented method is restricted to events of percussive instruments without determinate pitch. Events are detected in the audio signal and classified into instrument c...

This publication presents a new method for the detection and classification of un-pitched percussive instruments in real world musical signals. The derived information is an important pre-requisite for the creation of a musical score, i.e. automatic transcription, and for the automatic extraction of semantic meaningful meta-data, e.g. tempo and mus...