Towards Measuring Intonation Quality of Choir Recordings: a Case Study on Bruckner’S Locus Iste Christof Weiß, Sebastian J
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Towards Measuring Intonation Quality of Choir Recordings: A Case Study on Bruckner’s Locus Iste Christof Weiß, Sebastian J. Schlecht, Sebastian Rosenzweig, and Meinard Müller Overview An Intonation Cost Measure Unaccompanied vocal music is a central part Music scenario: 4 sopranos S1… S4 of Western art music, yet it requires excellent Anton Bruckner, 4 altos A1… A4 skills for singers to achieve proper intonation. Gradual Locus iste In this contribution, we analyze intonation part - 4 tenors T1…T4 4 deficiencies by introducing an intonation cost Multi-track recording [1] 16 individual singers polyphony measure that can be computed from choir re- 4 basses B1… B4 cordings and may help to assess the singers’ intonation quality. With our approach, we measure the deviation between the recor- Intonation Fixed grid: Fixed grid: Fixed grid: Adaptive grid: Adaptive grid: good intonation global offset global drift global drift global drift + local deviations ding’s local salient frequency content and an scenarios: adaptive reference grid based on the equal- tempered scale. The adaptivity introduces in- variance of the local intonation measure to global intonation drifts. In our experiments, we compute this measure for several recor- dings of Anton Bruckner’s choir piece Locus Iste. We demonstrate the robustness of the proposed measure by comparing scenarios of different complexity regarding the availa- adaptive grid, shift bility of aligned scores and multi-track recor- Intonation cost measure dings, as well as the number of singers per based on 12-tone part. Even without using score information, equal-tempered scale [2]: our cost measure shows interesting trends, thus indicating the potential of our method for real-world applications. with optimal, cost-minimizing grid shift and Gaussian deviation =16 cents Selected Scenarios Local Intonation Quality: Choral Singing Dataset [1] Global Intonation Quality: Different Recordings . Estimating frequencies 푓 and amplitudes 푎 from salience representation [3] Harmonic tones*, detuned 푑 = 0 cents . Different conditions / technical scenarios (A … D): . Score constraints for frequency estimation or no score constraints Synthetic Harmonic tones*, detuned 푑 = 15 cents . Individual tracks from multi-track recording [1] or mixed signal Examples Harmonic tones*, detuned 푑 = 30 cents . Only first voices of each part (S1, A1, T1, B1) or all voices Choir Samples SibeliusSounds (C) First voices 푥 , corrected 푥 fine Piano roll with deviations of first voices S1, A1, T1, B1 SATB1 note Choral (C) First voices 푥SATB1, corrected 푥 orig Singing (C) First voices 푥SATB1, original 푥 Dataset [1] orig (D) All voices 푥SATB, original 푥 All voices 푥SATB, with strong reverb Internet Archive 2013 (A) First voices S1, A1, T1, B1 (individual tracks), score constraints Philharmonia Vocalensemble 1979 Commercial Chor des Bayerischen Rundfunks 2012 Recordings Choir of St John's College 1996 NDR Chor Hamburg 2000 *16 partials with decaying amplitudes (B) First voices S1, A1, T1, B1 (individual tracks), no score constraints References & Acknowledgments [1] H. Cuesta, E. Gómez, A. Martorell, F. Loáiciga: “Analysis of intonation in unison choir singing.” In Proceedings of the International Conference of Music Perception and Cognition (ICMPC), 2018. (C) First voices SATB1 (mixed signal), score constraints [2] T. Nakano, M. Goto, Y. Hiraga: “An automatic singing skill evaluation method for unknown melodies using pitch interval accuracy and vibrato features.” In Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH), 2006. [3] J. Salamon, E. Gómez: “Melody extraction from polyphonic music signals using pitch contour characteristics.” IEEE Transactions on Audio, Speech, and Language Processing, 2012. This work was supported by the German Research Foundation (DFG MU 2686/12-1). The Internatio- (D) All voices SATB (mixed signal), score constraints nal Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander-Universität Erlan- gen-Nürnberg (FAU) and Fraunhofer Institut für Integrierte Schaltungen IIS. We thank Helena Cuesta and colleagues from UPF Barcelona for creating and publishing the Choral Singing Dataset..