Recognition of pen-based music notation with finite-state machines

This work presents a statistical model to recognize pen-based music compositions using stroke recognition algorithms and finite-state machines. The series of strokes received as input is mapped onto a stochastic representation, which is combined with a formal language that describes musical symbols in terms of stroke primitives. Then, a Probabilistic Finite-State Automaton is obtained, which defines probabilities over the set of musical sequences. This model is eventually crossed with a semantic language to avoid sequences that does not make musical sense. Finally, a decoding strategy is applied in order to output a hypothesis about the musical sequence actually written. Comprehensive experimentation with several decoding algorithms, stroke similarity measures and probability density estimators are tested and evaluated following different metrics of interest. Results found have shown the goodness of the proposed model, obtaining competitive performances in all metrics and scenarios considered.This work was supported by the Spanish Ministerio de Educación, Cultura y Deporte through a FPU Fellowship (Ref. AP2012–0939) and the Spanish Ministerio de Economía y Competitividad through the TIMuL Project (No. TIN2013-48152-C2-1-R, supported by UE FEDER funds)

Melody Harmonization

Vedci z oboru informačných technológií oddávna považovali hudbu za obzvlášť zaujímavé umenie. Pravdou je, že história hudby tvorenej počítačom je skoro tak dlhá ako história počítačovej vedy. Programy pre komponovanie, alebo tvorenie hudby" na rôznych úrovniach procesu kompozície boli vyvíjané už od 50tych rokov minulého storočia. Táto bakalárska práca uvádza hlavné prístupy v oblasti automatickej harmonizácie t.j. Problém produkovania hudobného aranžmá (nôt) z daných melódií, a sústreďuje sa na najpoužívanejšie techniky jeho riešenia. Hlavným cieľom tejto práce je návrh a implementácia softvérového systému pre automatickú harmonizáciu, ktorý by mal byť schopný naučiť sa pravidlá harmónie z databázy midi súborov. V tejto práci popíšem existujúce harmonizačné systémy a ďalej sa zameriam hlavne na princípy strojového učenia - teóriu a aplikáciu umelých neurónových sietí a ich použitie pre harmonizáciu.Computer scientists have long been considering music as a particularly interesting art Indeed, the history of computer music is almost as long as the history of computer science. Programs to compose music, or to make music" at various levels of the composition process have been designed since the 50s. This bachelor's thesis surveys the main approaches in the field of automatic harmonization, i.e. the problem of producing musical arrangements (scores) from given melodies, and focuses on the most widely used techniques to do so. The main goal of this paper is the issue of design and implementation of a software system for an automatic music harmonization which should learn the rules of harmony from the database of midi file. In the paper. In this thesis I describe existing systems for harmonization and furthermore I focus mainly on principles of machine learning - theory and application of Artificial Neural Networks and their use for harmonization.

L-Music: uma abordagem para composição musical assistida usando L-Systems

Generative music systems have been researched for an extended period of time. The scientific corpus of this research field is translating, currently, into the world of the everyday musician and composer. With these tools, the creative process of writing music can be augmented or completely replaced by machines. The work in this document aims to contribute to research in assisted music composition systems. To do so, a review on the state of the art of these fields was performed and we found that a plethora of methodologies and approaches each provide their own interesting results (to name a few, neural networks, statistical models, and formal grammars). We identified Lindenmayer Systems, or L-Systems, as the most interesting and least explored approach to develop an assisted music composition system prototype, aptly named L-Music, due to the ability of producing complex outputs from simple structures. L-Systems were initially proposed as a parallel string rewriting grammar to model algae plant growth. Their applications soon turned graphical (e.g., drawing fractals), and eventually they were applied to music generation. Given that our prototype is assistive, we also took the user interface and user experience design into its well-deserved consideration. Our implemented interface is straightforward, simple to use with a structured visual hierarchy and flow and enables musicians and composers to select their desired instruments; select L-Systems for generating music or create their own custom ones and edit musical parameters (e.g., scale and octave range) to further control the outcome of L-Music, which is musical fragments that a musician or composer can then use in their own works. Three musical interpretations on L-Systems were implemented: a random interpretation, a scale-based interpretation, and a polyphonic interpretation. All three approaches produced interesting musical ideas, which we found to be potentially usable by musicians and composers in their own creative works. Although positive results were obtained, the developed prototype has many improvements for future work. Further musical interpretations can be added, as well as increasing the number of possible musical parameters that a user can edit. We also identified the possibility of giving the user control over what musical meaning L-Systems have as an interesting future challenge.Sistemas de geração de música têm sido alvo de investigação durante períodos alargados de tempo. Recentemente, tem havido esforços em passar o conhecimento adquirido de sistemas de geração de música autónomos e assistidos para as mãos do músico e compositor. Com estas ferramentas, o processo criativo pode ser enaltecido ou completamente substituído por máquinas. O presente trabalho visa contribuir para a investigação de sistemas de composição musical assistida. Para tal, foi efetuado um estudo do estado da arte destas temáticas, sendo que foram encontradas diversas metodologias que ofereciam resultados interessantes de um ponto de vista técnico e musical. Os sistemas de Lindenmayer, ou L-Systems, foram selecionados como a abordagem mais interessante, e menos explorada, para desenvolver um protótipo de um sistema de composição musical assistido com o nome L-Music, devido à sua capacidade de produzirem resultados complexos a partir de estruturas simples. Os L-Systems, inicialmente propostos para modelar o crescimento de plantas de algas, são gramáticas formais, cujo processo de reescrita de strings acontece de forma paralela. As suas aplicações rapidamente evoluíram para interpretações gráficas (p.e., desenhar fractais), e eventualmente também foram aplicados à geração de música. Dada a natureza assistida do protótipo desenvolvido, houve uma especial atenção dada ao design da interface e experiência do utilizador. Esta, é concisa e simples, tendo uma hierarquia visual estruturada para oferecer uma orientação coesa ao utilizador. Neste protótipo, os utilizadores podem selecionar instrumentos; selecionar L-Systems ou criar os seus próprios, e editar parâmetros musicais (p.e., escala e intervalo de oitavas) de forma a gerarem excertos musicais que possam usar nas suas próprias composições. Foram implementadas três interpretações musicais de L-Systems: uma interpretação aleatória, uma interpretação à base de escalas e uma interpretação polifónica. Todas as interpretações produziram resultados musicais interessantes, e provaram ter potencial para serem utilizadas por músicos e compositores nos seus trabalhos criativos. Embora tenham sido alcançados resultados positivos, o protótipo desenvolvido apresenta múltiplas melhorias para trabalho futuro. Entre elas estão, por exemplo, a adição de mais interpretações musicais e a adição de mais parâmetros musicais editáveis pelo utilizador. A possibilidade de um utilizador controlar o significado musical de um L-System também foi identificada como uma proposta futura relevante

Creating Persian-like music using computational intelligence

Dastgāh are modal systems in traditional Persian music. Each Dastgāh consists of a group of melodies called Gushé, classified in twelve groups about a century ago (Farhat, 1990). Prior to that time, musical pieces were transferred through oral tradition. The traditional music productions revolve around the existing Dastgāh, and Gushe pieces. In this thesis computational intelligence tools are employed in creating novel Dastgāh-like music.There are three types of creativity: combinational, exploratory, and transformational (Boden, 2000). In exploratory creativity, a conceptual space is navigated for discovering new forms. Sometimes the exploration results in transformational creativity. This is due to meaningful alterations happening on one or more of the governing dimensions of an item. In combinational creativity new links are established between items not previously connected. Boden stated that all these types of creativity can be implemented using artificial intelligence.Various tools, and techniques are employed, in the research reported in this thesis, for generating Dastgāh-like music. Evolutionary algorithms are responsible for navigating the space of sequences of musical motives. Aesthetical critics are employed for constraining the search space in exploratory (and hopefully transformational) type of creativity. Boltzmann machine models are applied for assimilating some of the mechanisms involved in combinational creativity. The creative processes involved are guided by aesthetical critics, some of which are derived from a traditional Persian music database.In this project, Cellular Automata (CA) are the main pattern generators employed to produce raw creative materials. Various methodologies are suggested for extracting features from CA progressions and mapping them to musical space, and input to audio synthesizers. The evaluation of the results of this thesis are assisted by publishing surveys which targeted both public and professional audiences. The generated audio samples are evaluated regarding their Dastgāh-likeness, and the level of creativity of the systems involved

Stochastic processes and probability theory in music.

This dissertation examines the connections between music and mathematics with particular reference to Markov chains and generative grammars. The main purpose of this study is to investigate how mathematical concepts can help to control, create and analyse music material. The core part of this study is software that allows one to compose music with Markov Chains and generative grammars. The study will explore the on-going influence of such tools on composers and their relationship to musical sources and inspirations. An in-depth analysis of existing literature, music material and composition tools was conducted. Using comparative case studies, this research explored the significant role of mathematics in music in the twentieth and twenty-first centuries. The evolving role of stochastic concepts in music was presented. The next step was to develop a useful tool that would allow composers to apply Markov chains and generative grammars in their compositions. The web application that resulted was called Stochastic Composer. To evaluate this application five composers were invited to test it. The results include over one hundred samples of music material that were later analysed and used to improve the software. This dissertation offers insight into applications of various mathematical concepts in music. The Stochastic Composer software, available online, proved to be a useful tool in a compositional process

Non-Standard Sound Synthesis with Dynamic Models

Full version unavailable due to 3rd party copyright restrictions.This Thesis proposes three main objectives: (i) to provide the concept of a new generalized non-standard synthesis model that would provide the framework for incorporating other non-standard synthesis approaches; (ii) to explore dynamic sound modeling through the application of new non-standard synthesis techniques and procedures; and (iii) to experiment with dynamic sound synthesis for the creation of novel sound objects. In order to achieve these objectives, this Thesis introduces a new paradigm for non-standard synthesis that is based in the algorithmic assemblage of minute wave segments to form sound waveforms. This paradigm is called Extended Waveform Segment Synthesis (EWSS) and incorporates a hierarchy of algorithmic models for the generation of microsound structures. The concepts of EWSS are illustrated with the development and presentation of a novel non-standard synthesis system, the Dynamic Waveform Segment Synthesis (DWSS). DWSS features and combines a variety of algorithmic models for direct synthesis generation: list generation and permutation, tendency masks, trigonometric functions, stochastic functions, chaotic functions and grammars. The core mechanism of DWSS is based in an extended application of Cellular Automata. The potential of the synthetic capabilities of DWSS is explored in a series of Case Studies where a number of sound object were generated revealing (i) the capabilities of the system to generate sound morphologies belonging to other non-standard synthesis approaches and, (ii) the capabilities of the system of generating novel sound objects with dynamic morphologies. The introduction of EWSS and DWSS is preceded by an extensive and critical overview on the concepts of microsound synthesis, algorithmic composition, the two cultures of computer music, the heretical approach in composition, non- standard synthesis and sonic emergence along with the thorough examination of algorithmic models and their application in sound synthesis and electroacoustic composition. This Thesis also proposes (i) a new definition for “algorithmic composition”, (ii) the term “totalistic algorithmic composition”, and (iii) four discrete aspects of non-standard synthesis

iJazzARTIST: Intelligent Jazz Accompanist for Real-Time human-computer Interactive muSic improvisaTion

Κάποια από τα κυριότερα χαρακτηριστικά του αυτοσχεδιασμού σε πρότυπα τζαζ εκφράζονται μέσα από τη μουσική συνοδεία. Η συνεργασία μεταξύ ανθρώπων και τεχνητών συστημάτων για την επίτευξη αυτοσχεδιασμού σε πραγματικό χρόνο, υπό το πλαίσιο κοινής παρτιτούρας, αποτελεί ένα ιδιαίτερα ενδιαφέρον αντικείμενο μελέτης για τον τομέα της Ανάκτησης Μουσικής Πληροφορίας. Οι προϋπάρχουσες προσεγγίσεις που αφορούν στη διαδικασία της συνοδείας τζαζ αυτοσχεδιασμού, έχουν παρουσιάσει συστήματα που δε διαθέτουν την ικανότητα συμμόρφωσης με δυναμικά μεταβαλλόμενα περιβάλλοντα, εξαρτώμενα από τα αυτοσχέδια δεδομένα. Η παρούσα πτυχιακή εργασία παρουσιάζει ένα σύστημα συνοδείας, το οποίο διαθέτει την ικανότητα προσαρμογής τόσο στο τζαζ σόλο του μουσικού, όσο και τους περιορισμούς που έχουν προκαθοριστεί από την παρτιτούρα. Ο τεχνητός πράκτορας που αναπτύσσεται για το σκοπό αυτό, αποτελείται από δύο υποσυστήματα, ένα μοντέλο υπεύθυνο για την παραγωγή προβλέψεων που αφορούν το σόλο του μουσικού κι ένα δεύτερο υποσύστημα που παράγει την τελική μουσική συνοδεία, αξιοποιώντας την πληροφορία για τις προθέσεις του σολίστα που παρήγαγε το πρώτο μοντέλο. Και τα δύο προαναφερθέντα μοντέλα έχουν ως σχεδιαστική βάση τα Αναδρομικά Νευρωνικά Δίκτυα. Το σύνολο των δεδομένων που χρησιμοποιήθηκαν στην εκπαίδευση των μοντέλων υποβλήθηκαν σε επεξεργασία πολλών επιπέδων, συμπεριλαμβανομένης της πιθανολογικής βελτιστοποίησης, με στόχο τη διατήρηση και την επαύξηση της χρήσιμης πληροφορίας. Το τελικό σύστημα εξετάστηκε με τη χρήση δύο τζαζ προτύπων, παρουσιάζοντας προσαρμοστική ικανότητα ως προς τους αρμονικούς περιορισμούς, καθώς και ποικιλομορφία, εξαρτώμενη από τον αυτοσχεδιασμό του μουσικού. Τέλος, αναφέρονται κάποιες δυσκολίες που προέκυψαν, όπως επίσης και προτάσεις για περαιτέρω έρευνα.Some of the most essential characteristics of improvisation on jazz standards are reflected through the accompaniment. Given a lead sheet as common ground, the study of the collaborative process of music improvisation between a human and an artificial agent in a real time setting, is a scenario of great interest in the MIR domain. So far, the approaches concerning the jazz improvisation accompaniment procedure, have presented systems that lack the capability of performing the accompaniment generation task while at the same time adapting to dynamically variable constraints depending on new, improvised data. The thesis at hand, proposes a jazz accompaniment system capable of providing proper chord voicings to the solo, while complying with both the soloist's intentions as well as the previously defined constraints set by the lead sheet. The artificial agent consists of two sub-systems; a model responsible for predicting the human soloist's intentions and a second system performing the task of the accompaniment. The latter is achieved by modeling the artificial agent's predictions, after exploiting the information on the expectations of the human agent's intentions, previously calculated by the first model. Recurrent Neural Networks (RNNs) comprise both aforementioned models. The dataset used in the training process has undergone multi-staged processing including probabilistic refinement, aiming to keep and enrich the information which is requisite for the task. The system was tested on two cases of jazz standards, demonstrating ability of compliance with the harmonic constraints. Additionally, output variability depending on the solo improvisation has been indicated. Emerging limitations as well as potential future perspectives are discussed in the conclusion of this work

Algorithmic Compositional Methods and their Role in Genesis: A Multi-Functional Real-Time Computer Music System

Algorithmic procedures have been applied in computer music systems to generate compositional products using conventional musical formalism, extensions of such musical formalism and extra-musical disciplines such as mathematical models. This research investigates the applicability of such algorithmic methodologies for real-time musical composition, culminating in Genesis, a multi-functional real-time computer music system written for Mac OS X in the SuperCollider object-oriented programming language, and contained in the accompanying DVD. Through an extensive graphical user interface, Genesis offers musicians the opportunity to explore the application of the sonic features of real-time sound-objects to designated generative processes via different models of interaction such as unsupervised musical composition by Genesis and networked control of external Genesis instances. As a result of the applied interactive, generative and analytical methods, Genesis forms a unique compositional process, with a compositional product that reflects the character of its interactions between the sonic features of real-time sound-objects and its selected algorithmic procedures. Within this thesis, the technologies involved in algorithmic methodologies used for compositional processes, and the concepts that define their constructs are described, with consequent detailing of their selection and application in Genesis, with audio examples of algorithmic compositional methods demonstrated on the accompanying DVD. To demonstrate the real-time compositional abilities of Genesis, free explorations with instrumentalists, along with studio recordings of the compositional processes available in Genesis are presented in audiovisual examples contained in the accompanying DVD. The evaluation of the Genesis system’s capability to form a real-time compositional process, thereby maintaining real-time interaction between the sonic features of real-time sound objects and its selected algorithmic compositional methods, focuses on existing evaluation techniques founded in HCI and the qualitative issues such evaluation methods present. In terms of the compositional products generated by Genesis, the challenges in quantifying and qualifying its compositional outputs are identified, demonstrating the intricacies of assessing generative methods of compositional processes, and their impact on a resulting compositional product. The thesis concludes by considering further advances and applications of Genesis, and inviting further dissemination of the Genesis system and promotion of research into evaluative methods of generative techniques, with the hope that this may provide additional insight into the relative success of products generated by real-time algorithmic compositional processes