Publications Search Results

Now showing 1 - 8 of 8
  • Publication
    Score-informed analysis of tuning, intonation, pitch modulation, and dynamics in jazz solos
    ( 2017) ;
    Frieler, Klaus
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    Cano, Estefanía
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    Pfleiderer, Martin
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    Zaddach, Wolf-Georg
    Both the collection and analysis of large music repertoires constitute major challenges within musicological disciplines such as jazz research. Automatic methods of music analysis based on audio signal processing have the potential to assist researchers and to accelerate the transcription and analysis of music recordings significantly. In this paper, we propose a framework for analyzing improvised monophonic solos in multi-instrumental jazz recordings with special focus on reed and brass instruments. The analysis algorithms rely on prior score-information, which is taken from high quality manual solo transcriptions. Following an initial solo and accompaniment source separation, we propose algorithms for tone-wise extraction of fundamental frequency and intensity contours. Based on this fine-grained representation of recorded jazz solos, we perform several exploratory experiments motivated by questions relating to jazz research in order to analyze the use of expressive stylistic devices such as intonation, pitch modulation, and dynamics in jazz solos. The results show that a score-informed audio analysis of jazz recordings can provide valuable insights into the individual stylistic characteristics of jazz musicians.
  • Publication
    Deep learning for jazz walking bass transcription
    ( 2017) ;
    Balke, Stefan
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    Frieler, Klaus
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    Pfleiderer, Martin
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    In this paper, we focus on transcribing walking bass lines, which provide clues for revealing the actual played chords in jazz recordings. Our transcription method is based on a deep neural network (DNN) that learns a mapping from a mixture spectrogram to a salience representation that emphasizes the bass line. Furthermore, using beat positions, we apply a late-fusion approach to obtain beat-wise pitch estimates of the bass line. First, our results show that this DNN-based transcription approach outperforms state-of-the-art transcription methods for the given task. Second, we found that an augmentation of the training set using pitch shifting improves the model performance. Finally, we present a semi-supervised learning approach where additional training data is generated from predictions on unlabeled datasets.
  • Publication
    Midlevel analysis of monophonic jazz solos: A new approach to the study of improvisation
    ( 2016)
    Frieler, Klaus
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    Pfleiderer, Martin
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    Zaddach, Wolf-Georg
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    We present a novel approach to the analysis of jazz solos based on the categorisation and annotation of musical units on a middle level between single notes and larger form parts. A guideline during development was the hypothesis that these midlevel units (MLU) correspond to the improvising musicians' playing ideas and action plans. A system of categories was devised, comprising nine main categories (line, lick, theme, quote, melody, rhythm, expressive, fragment, void), 19 subcategories, and 41 sub-subcategories as well as syntactical rules to encode motivic relationships between units. A set of 140 monophonic jazz solos from various jazz styles (traditional, swing, bebop, hardbop, cool jazz, postbop, free jazz) was annotated manually, resulting in 4939 units in total. The median number of midlevel units is 32 per solo and 13.75 per chorus. The average duration is 2.25 s (SD = 1.57 s), in good agreement with the duration of the subjective present. Overall, the most common main category is lick (45.7% of all units), followed by line (31.5%), but distributions of the main MLU types differ significantly between styles and performers. About one quarter (M = 25.1%, SD = 15.3%) of the annotated units have motivic relations to preceding units. The mean length of consecutive motivic chains is 2.8 (SD = 1.4). The amount of motivic relations varies considerably between performers, but not between styles. Based on these first results, we discuss implications for jazz research and options for further applications of the proposed method.
  • Publication
    Score-informed analysis of intonation and pitch modulation in jazz solos
    ( 2015) ;
    Cano, Estefanía
    ;
    Frieler, Klaus
    ;
    Pfleiderer, Martin
    ;
    Zaddach, Wolf-Georg
    The paper presents new approaches for analyzing the characteristics of intonation and pitch modulation of woodwind and brass solos in jazz recordings. To this end, we use score-informed analysis techniques for source separation and fundamental frequency tracking. After splitting the audio into a solo and a backing track, a reference tuning frequency is estimated from the backing track. Next, we compute the fundamental frequency contour for each tone in the solo and a set of features describing its temporal shape. Based on this data, we first investigate, whether the tuning frequencies of jazz recordings changed over the decades of the last century. Second, we analyze whether the intonation is artist-specific. Finally, we examine how the modulation frequency of vibrato tones depends on contextual parameters such as pitch, duration, and tempo as well as the performing artist.
  • Publication
    Score-informed tracking and contextual analysis of fundamental frequency contours in trumpet and saxophone jazz solos
    ( 2014) ;
    Pfleiderer, Martin
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    Frieler, Klaus
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    Zaddach, Wolf-Georg
    In this paper, we propose a novel algorithm for score-informed tracking of the fundamental frequency over the duration of single tones. The tracking algorithm is based on a peak-picking algorithm over spectral magnitudes and ensures time-continuous f0-curves. From a set of 19 jazz solos from three saxophone and three trumpet players, we collected a set of 6785 f0-contours in total. We report the results of two exploratory analyses. First, we compared typical contour feature values among different jazz musicians and different instruments. Second, we analyzed correlations between contour features and contextual parameters that describe the metrical position, the in-phrase position, and additional properties of each tone in a solo.
  • Publication
    Dynamics in jazz improvisation - score-informed estimation and contextual analysis of tone intensities in trumpet and saxophone solos
    ( 2014) ;
    Cano, Estefanía
    ;
    Frieler, Klaus
    ;
    Pfleiderer, Martin
    In this paper, we aim at analyzing the use of dynamics in jazz improvisation by applying score-informed source separation and automatic estimation of note intensities. A set of 120 jazz solos taken from the Weimar Jazz Database covering many different jazz styles was manually transcribed and annotated by musicology and jazz students within the Jazzomat Research Project. In order to enrich these symbolic parameters with note-wise intensity annotations, the solo instrument tracks are extracted from the original audio files by applying a pitch-informed separation algorithm that uses the manual transcriptions as prior information. Subsequently, the magnitude envelope and spectral energy are analyzed in order to extract intensity measures for all note events in the solo. Next, we investigate how dynamics are used as a stylistic tool in jazz improvisation. To this end, we analyze how the note intensity values correlate with contextual information encoded in the note's pitch, duration, position within a musical phrase, perceptual accents, and structural markers. Additionally, we compare the use of dynamics among different instruments (alto and tenor saxophone, trumpet, and trombone). The results of this interdisciplinary study have implications for jazz research, jazz education, performance research, as well as for Music Information Retrieval fields such as automatic music transcription and source separation.
  • Publication
    Introducing the Jazzomat project - Jazz solo analysis using music information retrieval methods
    ( 2013) ;
    Frieler, Klaus
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    Pfleiderer, Martin
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    Zaddach, Wolf-Georg
    The JAZZOMAT project investigates the creative processes underlying jazz solo improvisations with the help of statistical and computational methods. To this end, a comprehensive and representative database of jazz solo transcription is being built up, and an open-source Python Library is developed for analysis purposes. Besides the general outline of the project and a description of our core feature module, we present three typical analysis tasks along with some preliminary and exemplary results.
  • Publication
    Introducing the Jazzomat project and the MeloPy library
    ( 2013)
    Frieler, Klaus
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    Pfleiderer, Martin
    ;
    ;
    Zaddach, Wolf-Georg