13 research outputs found

    Online score-informed source separation in polyphonic mixtures using instrument spectral patterns

    Get PDF
    [EN] Soundprism is a real-time algorithm to separate polyphonic music audio into source signals, given the musical score of the audio in advance. This paper presents a framework for a Soundprism implementation. A study of the sound quality of the online score-informed source separation is shown, although a real-time implementation is not carried out. The system is compound of two stages: (1) a score follower that matches a MIDI score position to each time frame of the musical performance; and (2) a source separator based on a nonnegative matrix factorization approach guided by the score. Real audio mixtures composed of an instrumental quartets were employed to obtain preliminary results of the proposed system.Ministerio de Economía y Competitividad. Grant Number: TEC2015-67387-C4-{1, 2, 3}-RMuñoz-Montoro, A.; Vera-Candeas, P.; Cortina, R.; Combarro, EF.; Alonso-Jordá, P. (2019). Online score-informed source separation in polyphonic mixtures using instrument spectral patterns. Computational and Mathematical Methods. 1-10. https://doi.org/10.1002/cmm4.1040S11

    An efficient musical accompaniment parallel system for mobile devices

    Full text link
    [EN] This work presents a software system designed to track the reproduction of a musical piece with the aim to match the score position into its symbolic representation on a digital sheet. Into this system, known as automated musical accompaniment system, the process of score alignment can be carried out real-time. A real-time score alignment, also known as score following, poses an important challenge due to the large amount of computation needed to process each digital frame and the very small time slot to process it. Moreover, the challenge is even greater since we are interested on handheld devices, i.e. devices characterized by both low power consumption and mobility. The results presented here show that it is possible to exploit efficiently several cores of an ARM(A (R)) processor, or a GPU accelerator (presented in some SoCs from NVIDIA) reducing the processing time per frame under 10 ms in most of the cases.This work was supported by the Ministry of Economy and Competitiveness from Spain (FEDER) under projects TEC2015-67387-C4-1-R, TEC2015-67387-C4-2-R and TEC2015-67387-C4-3-R, the Andalusian Business, Science and Innovation Council under project P2010-TIC-6762 (FEDER), and the Generalitat Valenciana PROMETEOII/2014/003Alonso-Jordá, P.; Vera-Candeas, P.; Cortina, R.; Ranilla, J. (2017). An efficient musical accompaniment parallel system for mobile devices. The Journal of Supercomputing. 73(1):343-353. https://doi.org/10.1007/s11227-016-1865-xS343353731Cont A, Schwarz D, Schnell N, Raphael C (2007) Evaluation of real- time audio-to-score alignment. In: Proc. of the International Conference on Music Information Retrieval (ISMIR) 2007, ViennaArzt A (2008) Score following with dynamic time warping. An automatic page-turner. Master’s Thesis, Vienna University of Technology, ViennaRaphael C (2010) Music plus one and machine learning. In: Proc. of the 27 th International Conference on Machine Learning, Haifa, pp 21–28Carabias-Ortí JJ, Rodríguez-Serrano FJ, Vera-Candeas P, Ruiz-Reyes N, Cañadas-Quesada FJ (2015) An audio to score alignment framework using spectral factorization and dynamic time warping. In: Proc. of the International Conference on Music Information Retrieval (ISMIR), Málaga, pp 742–748Cont A (2010) A coupled duration-focused architecture for real-time music-to-score alignment. IEEE Trans. Pattern Anal. Mach. Intell. 32(6):974–987Montecchio N, Orio N (2009) A discrete filterbank approach to audio to score matching for score following. In: Proc. of the International Conference on Music Information Retrieval (ISMIR), pp 495–500Puckette M (1995) Score following using the sung voice. In: Proc. of the International Computer Music Conference (ICMC), pp 175–178Duan Z, Pardo B (2011) Soundprism: an online system for score-informed source separation of music audio. IEEE J. Sel. Top. Signal Process. 5(6):1205–1215Cont A (2006) Realtime audio to score alignment for polyphonic music instruments using sparse non-negative constraints and hierarchical hmms. In: Proc. of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), ToulouseCuvillier P, Cont A (2014) Coherent time modeling of Semi-Markov models with application to realtime audio-to-score alignment. In Proc. of the 2014 IEEE International Workshop on Machine Learning for Signal Processing, p 16Joder C, Essid S, Richard G (2013) Learning optimal features for polyphonic audio-to-score alignment. IEEE Trans. Audio Speech Lang. Process. 21(10):2118–2128Dixon S (2005) Live tracking of musical performances using on-line time warping. In: Proc. International Conference on Digital Audio Effects (DAFx), Madrid, pp 92–97Hu N, Dannenberg RB, Tzanetakis G (2009) Polyphonic audio matching and alignment for music retrieval. In: Proc. of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp 185–188Orio N, Schwarz D (2001) Alignment of monophonic and polyphonic music to a score. In: Proc. International Computer Music Conference (ICMC)Alonso P, Cortina R, Rodríguez-Serrano FJ, Vera-Candeas P, Alonso-Gonzalez M, Ranilla J (2016) Parallel online time warping for real-time audio-to-score alignment in multi-core systems. J. Supercomput. doi: 10.1007/s11227-016-1647-5 (published online)Carabias-Ortí JJ, Rodríguez-Serrano FJ, Vera-Candeas P, Cañadas-Quesada FJ, Ruiz-Reyes N (2013) Constrained non-negative sparse coding using learnt instrument templates for realtime music transcription, Eng. Appl. Artif. Intell. 26(7):1671–1680Carabias-Ortí JJ, Rodríguez-Serrano FJ, Vera-Candeas P, Martínez-Muñoz D (2016) Tempo driven audio-to-score alignment using spectral decomposition and online dynamic time warping. ACM Trans. Intell. Syst. Technol. (accepted)FFTW (2016) http://www.fftw.org . Accessed July 2016NVIDIA CUDA Fast Fourier Transform library (cuFFT) (2016) http://developer.nvidia.com/cufft . Accessed July 2016The OpenMP API specification for parallel programming (2016) http://openmp.org . Accessed July 201

    Parallel Online Time Warping for Real-Time Audio-to-Score Alignment in Multi-core Systems

    Full text link
    [EN] The Audio-to-Score framework consists of two separate stages: pre- processing and alignment. The alignment is commonly solved through offline Dynamic Time Warping (DTW), which is a method to find the path over the distortion matrix with the minimum cost to determine the relation between the performance and the musical score times. In this work we propose a par- allel online DTW solution based on a client-server architecture. The current version of the application has been implemented for multi-core architectures (x86, x64 and ARM), thus covering either powerful systems or mobile devices. An extensive experimentation has been conducted in order to validate the software. The experiments also show that our framework allows to achieve a good score alignment within the real-time window by using parallel computing techniques.This work has been partially supported by Spanish Ministry of Science and Innovation and FEDER under Projects TEC2012-38142-C04-01, TEC2012-38142-C04-03, TEC2012-38142-C04-04, TEC2015-67387-C4-1-R, TEC2015-67387-C4-3-R, TEC2015-67387-C4-4-R, the European Union FEDER (CAPAP-H5 network TIN2014-53522-REDT), and the Generalitat Valenciana under Grant PROMETEOII/2014/003.Alonso-Jordá, P.; Cortina, R.; Rodríguez-Serrano, F.; Vera-Candeas, P.; Alonso-González, M.; Ranilla, J. (2017). Parallel Online Time Warping for Real-Time Audio-to-Score Alignment in Multi-core Systems. The Journal of Supercomputing. 73(1):126-138. https://doi.org/10.1007/s11227-016-1647-5S126138731Joder C, Essid S, Richard G (2011) A conditional random field framework for robust and scalable audio-to-score matching. IEEE Trans Speech Audio Lang Process 19(8):2385–2397McNab RJ, Smith LA, Witten IH, Henderson CL, Cunningham SJ (1996) Towards the digital music library: tune retrieval from acoustic input. In: DL 96: Proceedings of the first ACM international conference on digital libraries. ACM, New York, pp 11–18Dannenberg RB (2007) An intelligent multi-track audio editor. In: Proceedings of international computer music conference (ICMC), vol 2, pp 89–94Duan Z, Pardo B (2011) Soundprism: an online system for score-informed source separation of music audio. IEEE J Sel Topics Signal Process 5(6):1205–1215Dixon S (2005) Live tracking of musical performances using on-line time warping. In: Proceedings of the international conference on digital audio effects (DAFx), Madrid, Spain, pp 92–97Orio N, Schwarz D (2001) Alignment of monophonic and polyphonic music to a score. In: Proceedings of the international computer music conference (ICMC), pp 129–132Simon I, Morris D, Basu S (2008) MySong: automatic accompaniment generation for vocal melodies. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, New York, pp 725–734Rodriguez-Serrano FJ, Duan Z, Vera-Candeas P, Pardo B, Carabias-Orti JJ (2015) Online score-informed source separation with adaptive instrument models. J New Music Res Lond 44(2):83–96Arzt A, Widmer G, Dixon S (2008) Automatic page turning for musicians via real-time machine listening. In: Proceedings of the 18th European conference on artificial intelligence. IOS Press, Amsterdam, pp 241–245Carabias-Orti JJ, Rodriguez-Serrano FJ, Vera-Candeas P, Canadas-Quesada FJ, Ruiz-Reyes N (2015) An audio to score alignment framework using spectral factorization and dynamic time warping. In: 16th International Society for music information retrieval conference, pp 742–748Rodríguez-Serrano FJ, Menéndez-Canal J, Vidal A, Cañadas-Quesada FJ, Cortina R (2015) A DTW based score following method for score-informed sound source separation. In: Proceedings of the 12th sound and music computing conference 2015 (SMC-15), Ireland, pp 491–496Carabias-Ortí JJ, Rodríguez-Serrano FJ, Vera-Candeas P, Cañadas-Quesada FJ, Ruíz-Reyes N (2013) Constrained non-negative sparse coding using learnt instrument templates for realtime music transcription. Eng Appl Artif Intell 26(7):1671–1680Raphael C (2006) Aligning music audio with symbolic scores using a hybrid graphical model. Mach Learn 65:389–409Schreck-Ensemble (2001–2004) ComParser 1.42. http://home.hku.nl/~pieter.suurmond/SOFT/CMP/doc/cmp.html . Accessed Sept 2015Itakura F (1975) Minimum prediction residual principle applied to speech recognition. IEEE Trans Acoust Speech Signal Process 23:52–72Dannenberg R, Hu N (2003) Polyphonic audio matching for score following and intelligent audio editors. In: Proceedings of the international computer music conference. International Computer Music Association, San Francisco, pp 27–34Mueller M, Kurth F, Roeder T (2004) Towards an efficient algorithm for automatic score-to-audio synchronization. In: Proceedings of the 5th international conference on music information retrieval, Barcelona, SpainMueller M, Mattes H, Kurth F (2006) An efficient multiscale approach to audio synchronization. In: Proceedings of the 7th international conference on music information retrieval, Victoria, CanadaKaprykowsky H, Rodet X (2006) Globally optimal short-time dynamic time warping applications to score to audio alignment. In: IEEE ICASSP, Toulouse, France, pp 249–252Fremerey C, Müller M, Clausen M (2010) Handling repeats and jumps in score-performance synchronization. In: Proceedings of ISMIR, pp 243–248Arzt A, Widmer G (2010) Towards effective any-time music tracking. In: Proceedings of starting AI researchers symposium (STAIRS), Lisbon, Portugal, pp 24–3

    Real-time Soundprism

    Full text link
    [EN] This paper presents a parallel real-time sound source separation system for decomposing an audio signal captured with a single microphone in so many audio signals as the number of instruments that are really playing. This approach is usually known as Soundprism. The application scenario of the system is for a concert hall in which users, instead of listening to the mixed audio, want to receive the audio of just an instrument, focusing on a particular performance. The challenge is even greater since we are interested in a real-time system on handheld devices, i.e., devices characterized by both low power consumption and mobility. The results presented show that it is possible to obtain real-time results in the tested scenarios using an ARM processor aided by a GPU, when this one is present.This work has been supported by the "Ministerio de Economia y Competitividad" of Spain and FEDER under projects TEC2015-67387-C4-{1,2,3}-R.Muñoz-Montoro, AJ.; Ranilla, J.; Vera-Candeas, P.; Combarro, EF.; Alonso-Jordá, P. (2019). Real-time Soundprism. The Journal of Supercomputing. 75(3):1594-1609. https://doi.org/10.1007/s11227-018-2703-0S15941609753Alonso P, Cortina R, Rodríguez-Serrano FJ, Vera-Candeas P, Alonso-González M, Ranilla J (2017) Parallel online time warping for real-time audio-to-score alignment in multi-core systems. J Supercomput 73:126. https://doi.org/10.1007/s11227-016-1647-5Carabias-Orti JJ, Cobos M, Vera-Candeas P, Rodríguez-Serrano FJ (2013) Nonnegative signal factorization with learnt instrument models for sound source separation in close-microphone recordings. EURASIP J Adv Signal Process 2013:184. https://doi.org/10.1186/1687-6180-2013-184Carabias-Orti JJ, Rodriguez-Serrano FJ, Vera-Candeas P, Canadas-Quesada FJ, Ruiz-Reyes N (2015) An audio to score alignment framework using spectral factorization and dynamic time warping. In: 16th International Society for Music Information Retrieval Conference, pp 742–748Díaz-Gracia N, Cocaña-Fernández A, Alonso-González M, Martínez-Zaldívar FJ, Cortina R, García-Mollá VM, Alonso P, Ranilla J (2014) NNMFPACK: a versatile approach to an NNMF parallel library. In: Proceedings of the 2014 International Conference on Computational and Mathematical Methods in Science and Engineering, pp 456–465Díaz-Gracia N, Cocaña-Fernández A, Alonso-González M, Martínez-Zaldívar FJ, Cortina R, García-Mollá VM, Vidal AM (2015) Improving NNMFPACK with heterogeneous and efficient kernels for β\beta β -divergence metrics. J Supercomput 71:1846–1856. https://doi.org/10.1007/s11227-014-1363-yDriedger J, Grohganz H, Prätzlich T, Ewert S, Müller M (2013) Score-informed audio decomposition and applications. In: Proceedings of the 21st ACM International Conference on Multimedia, pp 541–544Duan Z, Pardo B (2011) Soundprism: an online system for score-informed source separation of music audio. IEEE J Sel Top Signal Process 5(6):1205–1215Duong NQ, Vincent E, Gribonval R (2010) Under-determined reverberant audio source separation using a full-rank spatial covariance model. IEEE Trans Audio Speech 18(7):1830–1840. https://doi.org/10.1109/TASL.2010.2050716Ewert S, Müller M (2011) Estimating note intensities in music recordings. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp 385–388Ewert S, Pardo B, Mueller M, Plumbley MD (2014) Score-informed source separation for musical audio recordings: an overview. IEEE Signal Process Mag 31:116–124. https://doi.org/10.1109/MSP.2013.2296076Fastl H, Zwicker E (2007) Psychoacoustics. Springer, BerlinGanseman J, Scheunders P, Mysore GJ, Abel JS (2010) Source separation by score synthesis. Int Comput Music Conf 2010:1–4Goto M, Hashiguchi H, Nishimura T, Oka R (2002) RWC music database: popular, classical and jazz music databases. In: ISMIR, vol 2, pp 287–288Goto M (2004) Development of the RWC music database. In: Proceedings of the 18th International Congress on Acoustics (ICA 2004), ppp 553–556Hennequin R, David B, Badeau R (2011) Score informed audio source separation using a parametric model of non-negative spectrogram. In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp 45–48. https://doi.org/10.1109/ICASSP.2011.5946324Itoyama K, Goto M, Komatani K et al (2008) Instrument equalizer for query-by-example retrieval: improving sound source separation based on integrated harmonic and inharmonic models. In: ISMIR. https://doi.org/10.1136/bmj.324.7341.827Marxer R, Janer J, Bonada J (2012) Low-latency instrument separation in polyphonic audio using timbre models. In: International Conference on Latent Variable Analysis and Signal Separation, pp 314–321Miron M, Carabias-Orti JJ, Janer J (2015) Improving score-informed source separation for classical music through note refinement. In: ISMIR, pp 448–454Ozerov A, Févotte C (2010) Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation. IEEE Trans Audio Speech Lang Process 18:550–563. https://doi.org/10.1109/TASL.2009.2031510Ozerov A, Vincent E, Bimbot F (2012) A general flexible framework for the handling of prior information in audio source separation. IEEE Trans Audio Speech Lang Process 20:1118–1133. https://doi.org/10.1109/TASL.2011.2172425Pätynen J, Pulkki V, Lokki T (2008) Anechoic recording system for symphony orchestra. Acta Acust United Acust 94:856–865. https://doi.org/10.3813/AAA.918104Raphael C (2008) A classifier-based approach to score-guided source separation of musical audio. Comput Music J 32:51–59. https://doi.org/10.1162/comj.2008.32.1.51Rodriguez-Serrano FJ, Duan Z, Vera-Candeas P, Pardo B, Carabias-Orti JJ (2015) Online score-informed source separation with adaptive instrument models. J New Music Res 44:83–96. https://doi.org/10.1080/09298215.2014.989174Rodriguez-Serrano FJ, Carabias-Orti JJ, Vera-Candeas P, Martinez-Munoz D (2016) Tempo driven audio-to-score alignment using spectral decomposition and online dynamic time warping. ACM Trans Intell Syst Technol 8:1–20. https://doi.org/10.1145/2926717Sawada H, Araki S, Makino S (2011) Underdetermined convolutive blind source separation via frequency bin-wise clustering and permutation alignment. IEEE Trans Audio Speech Lang Process 19(3):516–527. https://doi.org/10.1109/TASL.2010.2051355Vincent E, Araki S, Theis F et al (2012) The signal separation evaluation campaign (2007–2010): achievements and remaining challenges. Signal Process 92:1928–1936. https://doi.org/10.1016/j.sigpro.2011.10.007Vincent E, Bertin N, Gribonval R, Bimbot F (2014) From blind to guided audio source separation: how models and side information can improve the separation of sound. IEEE Signal Process Mag 31:107–115. https://doi.org/10.1109/MSP.2013.229744

    Music Scene-Adaptive Harmonic Dictionary for Unsupervised Note-Event Detection

    No full text
    corecore