Unattended acoustic sensor systems for noise monitoring in national parks

2017 Spring.Includes bibliographical references.Detection and classification of transient acoustic signals is a difficult problem. The problem is often complicated by factors such as the variety of sources that may be encountered, the presence of strong interference and substantial variations in the acoustic environment. Furthermore, for most applications of transient detection and classification, such as speech recognition and environmental monitoring, online detection and classification of these transient events is required. This is even more crucial for applications such as environmental monitoring as it is often done at remote locations where it is unfeasible to set up a large, general-purpose processing system. Instead, some type of custom-designed system is needed which is power efficient yet able to run the necessary signal processing algorithms in near real-time. In this thesis, we describe a custom-designed environmental monitoring system (EMS) which was specifically designed for monitoring air traffic and other sources of interest in national parks. More specifically, this thesis focuses on the capabilities of the EMS and how transient detection, classification and tracking are implemented on it. The Sparse Coefficient State Tracking (SCST) transient detection and classification algorithm was implemented on the EMS board in order to detect and classify transient events. This algorithm was chosen because it was designed for this particular application and was shown to have superior performance compared to other algorithms commonly used for transient detection and classification. The SCST algorithm was implemented on an Artix 7 FPGA with parts of the algorithm running as dedicated custom logic and other parts running sequentially on a soft-core processor. In this thesis, the partitioning and pipelining of this algorithm is explained. Each of the partitions was tested independently to very their functionality with respect to the overall system. Furthermore, the entire SCST algorithm was tested in the field on actual acoustic data and the performance of this implementation was evaluated using receiver operator characteristic (ROC) curves and confusion matrices. In this test the FPGA implementation of SCST was able to achieve acceptable source detection and classification results despite a difficult data set and limited training data. The tracking of acoustic sources is done through successive direction of arrival (DOA) angle estimation using a wideband extension of the Capon beamforming algorithm. This algorithm was also implemented on the EMS in order to provide real-time DOA estimates for the detected sources. This algorithm was partitioned into several stages with some stages implemented in custom logic while others were implemented as software running on the soft-core processor. Just as with SCST, each partition of this beamforming algorithm was verified independently and then a full system test was conducted to evaluate whether it would be able to track an airborne source. For the full system test, a model airplane was flown at various trajectories relative to the EMS and the trajectories estimated by the system were compared to the ground truth. Although in this test the accuracy of the DOA estimates could not be evaluated, it was show that the algorithm was able to approximately form the general trajectory of a moving source which is sufficient for our application as only a general heading of the acoustic sources is desired

Solução computacional para reconhecimento de harmonias musicais

Monografia (graduação)—Universidade de Brasília, Faculdade UnB Gama, Curso de Engenharia de Software, 2015.Atualmente, a música está num patamar único no que diz respeito às várias abordagens de se contemplar e se executar e, com isso, a tecnologia vem cada vez mais sendo usada para otimizar os processos musicais. Um dos exemplos de tecnologia são sistemas automáticos de transcrição de música que auxiliam o músico, substituindo por vezes de maneira significativa partituras, tablaturas e cifras. Esse presente trabalho tem como objetivo desenvolver um protótipo de uma solução computacional para reconhecimento de harmonias musicais. Para tal fim, priorizou-se a modelagem matemática da solução: implementação da análise espectral da amostra de áudio, classificação em notas musicais, classificação em acordes com suportes a inversões, transição rítmica, reconhecimento dos padrões harmônicos ao longo do tempo, extração de tonalidade musical e o projeto do sistema solução sistematizado em engenharia de software. O desenvolvimento da solução se deu através de um método de desenvolvimento empírico, iterativo e incremental, utilizando a linguagem de programação Matlab para implementação. De fundamentos teóricos foram utilizados conceitos físicos do som, teoria musical, processamento de sinais e redes neurais artificiais. O desenvolvimento da solução permitiu o reconhecimento de acordes em tríades maiores, menores, aumentados, diminutos e invertidos em amostras isoladas de acordes gravados, transcrição automática de acordes ao longo do tempo e extração de tonalidade musical. O sistema solução final tem como requisito uma entrada de áudio de uma música tipoWAVE e duas saídas: acordes ao longo do tempo numa precisão de 1 segundo e a tonalidade da música. ___________________________________________________________________________ ABSTRACTCurrently, the music have been in top level with regard to various approaches to behold and run. The technology is increasingly becoming too an interaction approach with the musical processes. One of the technology examples are automatic music transcription systems that help the musician, improving significantly scores, tabs and chords. This present study aims to develop a prototype of computational solution for recognition of musical harmonies. For this purpose, implementations of spectral analysis of the audio sample, classification of musical notes, chord classification with support inversion, recognition of rhythmic and harmonic transition patterns over time and extraction of musical tonalities were made. The development of the solution was through a method of empirical, iterative and incremental cicles, using Matlab programming language for implementation. Of theoretical foundations were used physical concepts of sound, music theory, signal processing and artificial neural networks. The development solution has allowed the recognition of the chord triads in larger, smaller, increased, and miniature inverted in isolated samples of recorded chords, chord automatic transcription over time and extraction of musical tone

A transient detection algorithm for audio using iterative analysis of STFT

We propose an iterative algorithm to detect transient segments in audio signals. Short time Fourier transform(STFT) is used to detect rapid local changes in the audio signal. The algorithm has two steps that iteratively - (a) calculate a function of the STFT and (b) build a transient signal. A dynamic thresholding scheme is used to locate the potential positions of transients in the signal. The iterative procedure ensures that genuine transients are built up while the localised spectral noise are suppressed by using an energy criterion. The extracted transient signal is later compared to a ground truth dataset. The algorithm performed well on two databases. On the EBU-SQAM database of monophonic sounds, the algorithm achieved an F-measure of 90% while on our database of polyphonic audio an F-measure of 91% was achieved. This technique is being used as a preprocessing step for a tempo analysis algorithm and a TSR (Transients + Sines + Residue) decomposition scheme

Contribution to the problem of computer-aided orchestration with the support of audio descriptors

Orientadores: Jônatas Manzolli, Stéphan Oliver SchaubTese (doutorado) - Universidade Estadual de Campinas, Instituto de ArtesResumo: Dentro da linha de pesquisa em Suportes instrumentais e materiais para composição e, em especial, à orquestração assistida por computador, a Tese descreve um estudo sobre o processo de combinação instrumental utilizando-se um ambiente computacional projetado com descritores de áudio, o qual denominamos como "Sound Shizuku Composition" ou SSC. Para tanto, implementamos o SSC em Pure Data (PD), utilizando a biblioteca de funções "PDescriptors" para analisar as características sonoras de um banco de dados de arquivos de áudio com diversos instrumentos musicais e técnicas expandidas. A pesquisa apoia-se, principalmente, em três aspectos fundamentais: a) o estudo de descritores de áudio como ferramenta de análise sonora à orquestração musical assistida por computador; b) a análise de obras e procedimentos desenvolvidos por compositores que servirão de referência para o desenvolvimento de modelos de escritura e; c) a criação de estudos composicionais, nos quais serão testadas as hipóteses de orquestração. A partir do estudo sobre os descritores de áudio como ferramenta de análise, item "a", a etapa centrou-se na geração de um universo de combinações instrumentais descrito a partir de suas características sonoras. Tal procedimento auxilia a tomada de decisão relacionada à orquestração e técnicas expandidas. Com relação ao item "b", utilizamos os descritores de áudio para analisar as características sonoras das seguintes obras: o Primeiro Movimento das "Quattro Pezzi per Orchestra", de Giacinto Scelsi; as três peças solo "Guero", "Pression" e "Dal Niente - Interieur III", de Helmut Lachenmann e; "Reflexões", de Jônatas Manzolli. No que refere-se ao item "c", apresentamos um portfólio de composições musicais, cujo planejamento orquestral baseou-se no diálogo entre os resultados obtidos a partir dos estudos dos descritores de áudio com as análises das obras dos compositores de referência. Espera-se que todo o processo de pesquisa aqui reportado contribua com o desenvolvimento na área de orquestração musical assistida por computador, estabelecendo uma mescla mais refinada da diversidade sonora enquanto um método de combinação de instrumentos musicais e técnicas expandidasAbstract: This Thesis describes an investigation into the instrumental combination process using a computing environment designed with audio descriptors, which we refer to as Sound Shizuku Composition or SSC. To this end, we implemented the SSC in PureData programming language (PD) using the library of functions "PDescriptors" to analyze the sound characteristics of a sound database with a myriad of musical instruments and extended techniques. The research relies mainly on three fundamental aspects: a) the study of audio descriptors such as sound analysis tool for computer-assisted musical orchestration; b) the analysis of works by composers and procedures developed to serve as a reference for the development of compositional models; c) the creation of compositional studies, in which the orchestrations will be tested. From the study on the audio descriptors as an analytical tool, item "a" focused on the generation of a universe of instrumental combinations described from their sonic characteristics. This procedure helps the decision making related to the orchestration and extended techniques. Regarding to item "b", we use the audio descriptors to analyze the sound characteristics of the following works: the First Movement of "Quattro Pezzi per Orchestra" by Giacinto Scelsi; the three solo pieces "Guero", "Pression" and "Dal Niente - Interieur III" by Helmut Lachenmann and "Reflexões" by Jônatas Manzolli. As refers to the item "c", we present a portfolio of original musical works, whose orchestral planning was based on the dialogue between the results obtained from studies of audio descriptors with the analysis of the works of reference composers. It is expected that the whole process of research reported here will increase the field of computer-assisted musical orchestration research area, establishing a more refined blend of sound diversity as a method of combination of musical instruments and extended techniquesDoutoradoProcessos CriativosDoutor em Música2011/23972-2FAPES

“lana Tai - No Dia Em Que Nasceu Uma Aquarela”: Composing Via Audio Descriptors [lana Tai-no Dia Em Que Nasceu Uma Aquarela: Diário De Bordo De Uma Composição A Partir De Descritores De áudio]

This article is a review of a music creative processes in which it was applied compositional strategies combined to sound spectral analysis based on audio descriptors. This procedure supported the creation of the work “Lana Tai-no dia em que nasceu uma aquarela” for string orchestra. For that, some instrumental mixtures and orchestration were made using a Sound DataBase. In this particular case, a virtual environment in Pure Data (PD) software, using the library for analysis fucntions PDescriptors, analyzed some potential orchestral settings. All the results, issues and compositional reflections were used to create “Lana Tai-no dia em que nasceu uma aquarela”. This approach rises up a new contribution in the development of research in both creative processes and the creation of new unpublished works. © 2015, Universidade Federal de Minas Gerais. All rights reserved.201532338363Assayag, G., Rueda, C., Laurson, M., Agon, C., Delerue, O., Computer-assisted composition at ircam: From patchwork to openmusic (1999) Computer Music Journal, 23 (3), pp. 59-72Ballet, G., Borghesi, R., Hoffmann, P., Lévy, F., Studio Online 3.0: An Internet “Killer Application” for Remote Access to IRCAM Sounds and Processing tools (1999) Journées d’Informatique Musicale, , FranceBarbedo, J.G.A., Lopes, A., Automatic genre classification of musical signals (2007) EURASIP Journal on Applied Signal Processing, 2007 (1), 157pBerlioz, H., (1844) Treatise on Instrumentation by Hector Berlioz and Richard Strauss, , translated by Theodore Front, published by Edwin F. Kalmus, NY, NY 1948Bogdanov, D., Wack, N., Gómez, E., Essentia: An audio analysis library for music information retrieval (2013) Proceedings of ISMIRBoulez, P., Timbre and composition-timbre and language (1987) Contemporary Music Review, 2, pp. 161-171. , Translated by R. RobertsonByrd, D., Fingerhut, M., The History of ISMIR-A Short Happy Tale (2002) D-Lib Magazine, 8 (11)Carpentier, G., (2008) Approche Computationelle De l’orchestration Musicale-Optimization multicritère Sous Contraintes De Combinaisons Instrumentales Dans De Grandes Banques De Sons, , Ph.D. Thesis, University Pierre et Marie Curie, ParisCartwright, M., Pardo, B., Social-Eq: Crowdsourcing An Equalization Descriptor Map (2013) N. 14O International Conference-Ismir, , Curitiba-BrazilDeshpande, H., Singh, R., Nam, U., Classification of music signals in the visual domain (2001) Proceedings of the Conference on Digital Audio Effects, pp. 1-4Dieleman, S., Schrauwen, B., Multiscale Approaches To Music Audio Feature Learning (2013) 14O International Conference-Ismir-Curitiba-BrazilDownie, J.S., Ehmann, A.F., Bay, M., Jones, M.C., The Music Information Retrieval Evaluation eXchange: Some Observations and Insights (2010) International MIR Systems Evaluation Laboratory, , University of IllinoisEsling, P., Agon, C., Multiobjective Time Series Matching for Audio Classification and Retrieval (2013) IEEE Transactions on Audio, Speech, and Language Processing, 21 (10), pp. 2057-2072Esling, P., Agon, C., (2010) Composition of Sound Mixtures with Spectral Maquettes, , Ann Arbor, MI: MPublishing, University of Michigan LibraryEsling, P., Carpentier, G., Agon, C., Dynamic musical orchestration using genetic algorithms and a spectro-temporal description of musical instruments (2010) Applications of Evolutionary Computation, pp. 371-380. , SpringerFujishima, T., (1999) Realtime Chord Recognition of Musical Sound: A System Using Common Lisp Music, 4p. , CCRMA, Stanford UniversityGomez, E., (2006) Tonal Description of Music Audio Signals, , Ph.D. dissertation, MTG, Universitat Pompeu Fabra, Barcelona, SpainHarvey, J., The Composer’s View: Atonality (1980) The Musical Times, 699pHummel, T.A., Simulation of human voice timbre by orchestration of acoustic music instruments (2005) Proceedings of ICMC, 185pLambrou, T., Kudumakis, P., Speller, R., Sandler, M., Linney, A., Classification of audio signals using statistical features on time and wavelet transform domains. Acoustics, Speech and Signal Processing (1998) Proceedings of the 1998 IEEE International Conference On, 6, pp. 3621-3624Laurson, M., Kuuskankare, M., PWGL: A Novel Visual Language based on Common Lisp, CLOS and OpenGL (2002) Proceedings of International Computer Music Conference, pp. 142-145. , Gothenburg, SwedenMalt, M., Jourdan, E., .Descriptors: A library for real-time descriptors analysis (2008) 5Th Sound and Music Computing Conference, , Berlin, AllemagneMalt, M., Jourdan, E., (2009) Real-Time Uses of Low Level Sound Descriptors as Event Detection Functions Using the Max/Msp Zsa.Descriptors Library, , SBCM, Recife, BrazilManzolli, J., (1988) Um Modelo Matemático Para Timbre Orquestral, , Dissertação de mestrado, IMECC, Unicamp(2005) Creation and Perception of a Contemporary Musical Work: The Angel of Death by Roger Reynolds, , Ircam, ParisMonteiro, A., Criação e Performance Musical no Contexto dos Instrumentos Digitais (2012) Dissertação De Mestrado. Núcleo Interdisciplonar De Comunicação Sonora-Nics/Unicamp, 159p. , Universidade Estadual CampinasPadovani, J., Ferraz, S., (2011) Proto-História, Evolução E Situação Atual Das Técnicas Estendidas Na Criação Musical E Na Performance, 11. , Música HodiePampalk, E., Computational models of music similarity and their application in music information retrieval (2006) Tese De Doutorado, , Austria: Vienna University of TechnologyPeeters, G., (2004) A Large Set of Audio Features for Sound Description (Similarity and Classification) in the CUIDADO Project, CUIDADO, , Project ReportPereira, E., (2009) Estudos Sobre Uma Ferramenta De Classificação Musical, 65p. , Dissertação de Mestrado-Universidade Estadual Campinas, FEECPires, A.S., (2011) Métodos De segmentação Musical Baseados Em Descritores Sonoros, , Dissertação de Mestrado, Universidade de São PauloPiston, W., Orchestration (1955) W Norton & Company IncorporatedPuckette, M.S., (1996) Pure Data. Proceedings, International Computer Music Conference, pp. 269-272. , San Francisco: International Computer Music AssociationPsenicka, D., Sporch: An algorithm for orchestration based on spectral analyses of recorded sounds (2003) Proceedings of ICMC, 184pRose, F., Hetrick, J.E., Enhancing orchestration technique via spectrally based linear algebra methods (2009) Computer Music Journal, 33 (1), pp. 32-41Rimsky-Korsakov, N., Principles of Orchestration (1922) Traduzido Por Edward Agate, , Maximilian Steinberg, New York: Dover PublicationsSchafer, M., (1997) A afinação Do Mundo. Título Original Em inglês: The Tuning of The World, , Editora UNESPSheh, A., Ellis, D.P.W., Chord segmentation and recognition using EM-trained hidden Markov models (2003) International Conference on MIR, , Baltimore, USAShepard, R.N., Structural representations of musical pitch (1982) The Psychology of Music, , Deutsch, D., editor, First Edition. Swets & ZeitlingerTheodoridis, S., (2009) Pattern Recognition, 967p. , KOUTROUMBAS, Academic pressThoshkahna, B., Nsabimana, F., Ramakrishnan, K.R., A Transient Detection Algorithm For Audio Using Iterative Analysis Of Stft (2011) 12Th International Society for MIR ConferenceWang, A., (2003) An Industrial Strength Audio Search Algorithm, , ISMI