Automatically calculating tonal tension

Since the early years of the past century, many scholars have focused their efforts towards designing models to better understand the way listeners perceive musical tension. From the existing models, Lerdahl’s has shown strong correlations against tension judgements provided by human listeners and has been used to make accurate predictions of musical tension. However, a full automation of Lerdahl’s model of tension has not yet been made available. This paper presents a computational approach to automatically calculate musical tension according to Lerdahl’s model, with a publicly available implementation

Harmonic analysis of music using combinatory categorial grammar

FP7 grant 249520 (GRAMPLUS)Various patterns of the organization of Western tonal music exhibit hierarchical structure, among them the harmonic progressions underlying melodies and the metre underlying rhythmic patterns. Recognizing these structures is an important part of unconscious human cognitive processing of music. Since the prosody and syntax of natural languages are commonly analysed with similar hierarchical structures, it is reasonable to expect that the techniques used to identify these structures automatically in natural language might also be applied to the automatic interpretation of music. In natural language processing (NLP), analysing the syntactic structure of a sentence is prerequisite to semantic interpretation. The analysis is made difficult by the high degree of ambiguity in even moderately long sentences. In music, a similar sort of structural analysis, with a similar degree of ambiguity, is fundamental to tasks such as key identification and score transcription. These and other tasks depend on harmonic and rhythmic analyses. There is a long history of applying linguistic analysis techniques to musical analysis. In recent years, statistical modelling, in particular in the form of probabilistic models, has become ubiquitous in NLP for large-scale practical analysis of language. The focus of the present work is the application of statistical parsing to automatic harmonic analysis of music. This thesis demonstrates that statistical parsing techniques, adapted from NLP with little modification, can be successfully applied to recovering the harmonic structure underlying music. It shows first how a type of formal grammar based on one used for linguistic syntactic processing, Combinatory Categorial Grammar (CCG), can be used to analyse the hierarchical structure of chord sequences. I introduce a formal language similar to first-order predicate logical to express the hierarchical tonal harmonic relationships between chords. The syntactic grammar formalism then serves as a mechanism to map an unstructured chord sequence onto its structured analysis. In NLP, the high degree of ambiguity of the analysis means that a parser must consider a huge number of possible structures. Chart parsing provides an efficient mechanism to explore them. Statistical models allow the parser to use information about structures seen before in a training corpus to eliminate improbable interpretations early on in the process and to rank the final analyses by plausibility. To apply the same techniques to harmonic analysis of chord sequences, a corpus of tonal jazz chord sequences annotated by hand with harmonic analyses is constructed. Two statistical parsing techniques are adapted to the present task and evaluated on their success at recovering the annotated structures. The experiments show that parsing using a statistical model of syntactic derivations is more successful than a Markovian baseline model at recovering harmonic structure. In addition, the practical technique of statistical supertagging serves to speed up parsing without any loss in accuracy. This approach to recovering harmonic structure can be extended to the analysis of performance data symbolically represented as notes. Experiments using some simple proof-of-concept extensions of the above parsing models demonstrate one probabilistic approach to this. The results reported provide a baseline for future work on the task of harmonic analysis of performances

Tension-driven Automatic Music Generation

The Ancient Greeks are one of the first civilisations we know of to have created algorithms to compose music. Since then, algorithmic techniques have vastly improved with increasingly sophisticated computers. In the last two decades, much research in this area has focused on two goals: designing algorithms which generate music as close as possible to that of human composers and implementing those algorithms to automatically generate music in interactive scenarios, such as video games. To meet these goals, automatically generated music should: - focus on higher-level concepts, such as musical tension, - have long-term structure, and - be able to adapt to changes in real time. Combining these three requirements is, however, a challenging task. This dissertation investigates three steps to overcome this challenge. First, we argue that Lerdahl’s model of musical tension is suited to the automatic generation of tonal music that has long-term structure and that matches a given tension profile. By means of an illustrative example, we review Lerdhal’s model and implement a novel computational system to automate it. Second, we show that an effective generation strategy is to combine statistical methods with both rule-based methods and generative grammars to create a music generation system. Third, we implement the system and evaluate it through a collection of computational tests and empirical studies. Our evaluation shows that: (1) the system works effectively in real time, as long as the input tension profiles do not contain too many steep transitions, (2) the hierarchical structure perceived by listeners matches the patterns intended by the system in the generated music, and (3) tension-changing input profiles are accurately matched by the generated music

Human-centred design of clinical auditory alarms

Auditory alarms are commonly badly designed, providing little to no information or guidance. In the healthcare context, the poor acoustics of alarms is one contributor for the noise problem. The goal of this thesis is to propose a human-centred methodology for the design of clinical auditory alarms, by making them less disruptive and more informative, thus improving the healthcare soundscape. It implements this methodology from concept to evaluation and validation, combining psychoacoustics with usability and user experience methods. Another aim of this research consisted in understanding the limitations and possibilities offered by online tools for scientific studies. Thus, different processes and methodologies were implemented, and corresponding results were discussed. To understand the acoustic healthcare environment, field visits, interviews, and surveys were performed with healthcare professionals. Additionally, sound pressure levels and frequency analysis of several surgeries in different hospitals provided specific sound design requirements, which were added to an existent body of knowledge on clinical alarm design. A second stage consisted in prototyping very simple sounds to comprehend which temporal and spectral parameters of sound could be manipulated to communicate clinical information. Parameters such as frequency, speed, onset, and rhythm were studied, and relations between subjective perception and physical parameters were established. In parallel, and heavily influenced by the new IEC 60601-1-8 - General requirements, tests and guidance for alarm systems in medical electrical equipment and medical electrical systems, a design strategy with auditory icons was created. This strategy intended to provide as much information as possible in an auditory alarm. To do so, it involved two main components: a priority pointer indicating the priority of the alarm; an auditory icon indicating the cause of the alarm. A third component indicating increasing or decreasing tendency of the vital sign was designed, but not validated with users. After online validation of the priority pointer and auditory icon for eight categories (cardiac, drug administration, ventilation, blood pressure, perfusion, oxygen, temperature, and power down), a new library of clinical auditory alarms is proposed.Os alarmes auditivos são habitualmente mal concebidos, dando poucas informações ou orientações perante a situação que despoletou o aviso. No contexto da saúde, a má acústica dos alarmes é um dos contribuidores para o problema do ruído. O objetivo desta tese é o de melhorar a paisagem sonora em ambientes clínicos, propondo uma metodologia centrada no Humano para o design de alarmes auditivos clínicos, tornando-os menos disruptivos e mais informativos. Essa metodologia é implementada desde o conceito até a avaliação e validação, combinando métodos da psicoacústica com métodos de usabilidade e experiência do utilizador. Outro objetivo desta investigação é o de compreender as limitações e possibilidades oferecidas pelas ferramentas online para estudos científicos. Assim, diversos processos e metodologias foram implementados, e os respetivos resultados são discutidos. Para compreender o ambiente acústico clínico, foram realizadas visitas de campo, entrevistas e inquéritos com profissionais de saúde. Além disso, avaliou-se o nível de pressão sonora e frequências de várias cirurgias em diferentes hospitais. Esta atividade forneceu requisitos específicos de design de som que foram adicionados a um corpo existente de conhecimento sobre design de alarmes clínicos. Uma segunda etapa consistiu na prototipagem de sons simples para compreender que parâmetros temporais e espectrais do som poderiam ser manipulados para comunicar informações clínicas. Parâmetros como frequência, velocidade, envelope e ritmo foram estudados, e as relações entre a perceção subjetiva e os parâmetros físicos foram estabelecidas. Paralelamente, e fortemente influenciado pela nova norma IEC 60601-1-8 - Requisitos gerais, testes e orientações para sistemas de alarme em equipamentos médicos elétricos e sistemas médicos elétricos, foi criada uma estratégia de design com ícones auditivos. Essa estratégia pretendia incorporar o máximo de informações num alarme auditivo. Para isso, envolveu dois componentes principais: um ponteiro de prioridade que indica a prioridade do alarme; e um ícone auditivo que indica a causa do alarme. Um terceiro componente de tendência (aumento ou diminuição do valor do sinal vital) foi criado, mas não validado com utilizadores. Após a validação do ponteiro de prioridade e ícone auditivo para oito categorias (cardíaco, administração de medicamentos, ventilação, pressão arterial, perfusão, oxigénio, temperatura e falha de equipamento), propõe-se uma nova biblioteca de alarmes auditivos clínicos

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes