83 research outputs found

    Automatic transcription of Turkish makam music

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    In this paper we propose an automatic system for transcribing/nmakam music of Turkey. We document the specific/ntraits of this music that deviate from properties that/nwere targeted by transcription tools so far and we compile/na dataset of makam recordings along with aligned microtonal/nground-truth. An existing multi-pitch detection algorithm/nis adapted for transcribing music in 20 cent resolution,/nand the final transcription is centered around the/ntonic frequency of the recording. Evaluation metrics for/ntranscribing microtonal music are utilized and results show/nthat transcription of Turkish makam music in e.g. an interactive/ntranscription software is feasible using the current/nstate-of-the-art.This work is partly supported by the European/nResearch Council under the European Union’s Seventh/nFramework Program, as part of the CompMusic project/n(ERC grant agreement 267583)

    Automatic transcription of traditional Turkish art music recordings: A computational ethnomusicology appraoach

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    Thesis (Doctoral)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2012Includes bibliographical references (leaves: 96-109)Text in English; Abstract: Turkish and Englishxi, 131 leavesMusic Information Retrieval (MIR) is a recent research field, as an outcome of the revolutionary change in the distribution of, and access to the music recordings. Although MIR research already covers a wide range of applications, MIR methods are primarily developed for western music. Since the most important dimensions of music are fundamentally different in western and non-western musics, developing MIR methods for non-western musics is a challenging task. On the other hand, the discipline of ethnomusicology supplies some useful insights for the computational studies on nonwestern musics. Therefore, this thesis overcomes this challenging task within the framework of computational ethnomusicology, a new emerging interdisciplinary research domain. As a result, the main contribution of this study is the development of an automatic transcription system for traditional Turkish art music (Turkish music) for the first time in the literature. In order to develop such system for Turkish music, several subjects are also studied for the first time in the literature which constitute other contributions of the thesis: Automatic music transcription problem is considered from the perspective of ethnomusicology, an automatic makam recognition system is developed and the scale theory of Turkish music is evaluated computationally for nine makamlar in order to understand whether it can be used for makam detection. Furthermore, there is a wide geographical region such as Middle-East, North Africa and Asia sharing similarities with Turkish music. Therefore our study would also provide more relevant techniques and methods than the MIR literature for the study of these non-western musics

    Automatic transcription of Turkish makam music

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    publicationstatus: publishedpublicationstatus: publishedpublicationstatus: publishedThe authors would like to thank Baris¸ Bozkurt for his adviceand for providing us with software-tools. E. Benetos is supported by a City University London Research Fellowship. This work is partly supported by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583)

    Incorporating pitch class profiles for improving automatic transcription of Turkish makam music

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    In this paper we evaluate the impact of including knowledge about scale material into a system for the transcription of Turkish makam music. To this end, we extend our previously presented approach by a refinement iteration that gives preference to note values present in the scale of the mode (i.e. makam). The information about the scalar material is provided in form of pitch class profiles, and they are imposed in form of a Dirichlet prior to our expanded probabilistic latent component analysis (PLCA) transcription system. While the inclusion of such a prior was supposed to focus the transcription system on musically meaningful areas, the obtained results are significantly improved only for recordings of certain instruments. In our discussion we demonstrate the quality of the obtained transcriptions, and discuss the difficulties caused for evaluation in the context of microtonal music

    Computational modeling of improvisation in Turkish folk music using Variable-Length Markov Models

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    The thesis describes a new database of uzun havas, a non-metered structured improvisation form in Turkish folk music, and a system, which uses Variable-Length Markov Models (VLMMs) to predict the melody in the uzun hava form. The database consists of 77 songs, encompassing 10849 notes, and it is used to train multiple viewpoints, where each event in a musical sequence are represented by parallel descriptors such as Durations and Notes. The thesis also introduces pitch-related viewpoints that are specifically aimed to model the unique melodic properties of makam music. The predictability of the system is quantitatively evaluated by an entropy based scheme. In the experiments, the results from the pitch-related viewpoints mapping 12-tone-scale of Western classical theory and 17 tone-scale of Turkish folk music are compared. It is shown that VLMMs are highly predictive in the note progressions of the transcriptions of uzun havas. This suggests that VLMMs may be applied to makam-based and non-metered musical forms, in addition to Western musical styles. To the best of knowledge, the work presents the first symbolic, machine-readable database and the first application of computational modeling in Turkish folk music.MSCommittee Chair: Parag Chordia; Committee Member: Gil Weinberg; Committee Member: Jason Freema

    A mechanical source of Turkish music from 18th-century London

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    A late eighteenth-century mechanical organ, built into a clock made by Henry Borrell of London, plays melodies that sound completely unlike those normally found on English domestic musical clocks. This article draws on the disciplines of historical musicology, ethnomusicology and horology to argue that these tunes derive directly from the repertory of the eighteenth-century Ottoman court. The melodies are analysed firstly in the context of the Ottoman repertory and then alongside contemporary European transcriptions of ‘exotic’ music, notably Edward Jones’s Lyric Airs. The distortion of ‘Turkish’ melodies in European representations is set within the wider context of orientalism and musical transculturation; this evidence is then brought to bear on interpreting music that may also be subject to mechanical distortion. The article ends with a consideration of how these earliest known sounding examples of Ottoman music may have arrived in London and its reception there

    Automatic transcription of Turkish microtonal music

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    Automatic music transcription, a central topic in music signal analysis, is typically limited to equal-tempered music and evaluated on a quartertone tolerance level. A system is proposed to automatically transcribe microtonal and heterophonic music as applied to the makam music of Turkey. Specific traits of this music that deviate from properties targeted by current transcription tools are discussed, and a collection of instrumental and vocal recordings is compiled, along with aligned microtonal reference pitch annotations. An existing multi-pitch detection algorithm is adapted for transcribing music with 20 cent resolution, and a method for converting a multi-pitch heterophonic output into a single melodic line is proposed. Evaluation metrics for transcribing microtonal music are applied, which use various levels of tolerance for inaccuracies with respect to frequency and time. Results show that the system is able to transcribe microtonal instrumental music at 20 cent resolution with an F-measure of 56.7%, outperforming state-of-the-art methods for the same task. Case studies on transcribed recordings are provided, to demonstrate the shortcomings and the strengths of the proposed method.QC 20161031</p

    Incorporating pitch class profiles for improving automatic transcription of Turkish makam music

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    publicationstatus: publishedpublicationstatus: publishedpublicationstatus: publishedEmmanouil Benetos is supported by a City University London Research Fellowship. Andre Holzapfel is supported by a Marie Curie Intra European Fellowship (PIEF-GA-2012-328379)

    A Corpus of Annotated Irish Traditional Dance Music Recordings: Design and Benchmark Evaluations

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    An emerging trend in music information retrieval (MIR) is the use of supervised machine learning to train automatic music transcription models. A prerequisite of adopting a machine learning methodology is the availability of annotated corpora. However, different genres of music have different characteristics and modelling these characteristics is an important part of creating state of the art MIR systems. Consequently, although some music corpora are available the use of these corpora is tied to the specific music genre, instrument type and recording context the corpus covers. This paper introduces the first corpus of annotations of audio recordings of Irish traditional dance music that covers multiple instrument types and both solo studio and live session recordings. We first discuss the considerations that motivated our design choices in developing the corpus. We then benchmark a number of automatic music transcription algorithms against the corpus. The underlying dataset for this research is available here at Github or here in Arrow
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