Construcción de un corpus de referencia para investigación en reconocimiento automático de partituras musicales

El Reconocimiento Óptico de Música es la rama de la inteligencia artificial que desarrolla sistemas que sean capaces extraer el contenido musical de una imagen de una partitura musical y transcribirlo a un formato que permita procesarlo fácilmente por un ordenador. La tendencia para el desarrollo de estos sistemas es usar técnicas de aprendizaje automático. Éstas técnicas son capaces de inferir la transcripción a partir de ejemplos correctos de la tarea, es decir, conjunto de pares (imagen, transcripción). Dada la complejidad de la música, para que estas técnicas arrojen resultados satisfactorios es necesario utilizar un conjunto muy grande. Es por ello que una buena medida es desarrollar sistemas que sean capaces de generar estos pares automáticamente, de forma que se pueda obtener un conjunto potencialmente ilimitado de ejemplos

Exploiting the Two-Dimensional Nature of Agnostic Music Notation for Neural Optical Music Recognition

State-of-the-art Optical Music Recognition (OMR) techniques follow an end-to-end or holistic approach, i.e., a sole stage for completely processing a single-staff section image and for retrieving the symbols that appear therein. Such recognition systems are characterized by not requiring an exact alignment between each staff and their corresponding labels, hence facilitating the creation and retrieval of labeled corpora. Most commonly, these approaches consider an agnostic music representation, which characterizes music symbols by their shape and height (vertical position in the staff). However, this double nature is ignored since, in the learning process, these two features are treated as a single symbol. This work aims to exploit this trademark that differentiates music notation from other similar domains, such as text, by introducing a novel end-to-end approach to solve the OMR task at a staff-line level. We consider two Convolutional Recurrent Neural Network (CRNN) schemes trained to simultaneously extract the shape and height information and to propose different policies for eventually merging them at the actual neural level. The results obtained for two corpora of monophonic early music manuscripts prove that our proposal significantly decreases the recognition error in figures ranging between 14.4% and 25.6% in the best-case scenarios when compared to the baseline considered.This research work was partially funded by the University of Alicante through project GRE19-04, by the “Programa I+D+i de la Generalitat Valenciana” through grant APOSTD/2020/256, and by the Spanish Ministerio de Universidades through grant FPU19/04957

Optical music recognition for homophonic scores with neural networks and synthetic music generation

The recognition of patterns that have a time dependency is common in areas like speech recognition or natural language processing. The equivalent situation in image analysis is present in tasks like text or video recognition. Recently, Convolutional Recurrent Neural Networks (CRNN) have been broadly applied to solve these tasks in an end-to-end fashion with successful performance. However, its application to Optical Music Recognition (OMR) is not so straightforward due to the presence of different elements sharing the same horizontal position, disrupting the linear flow of the timeline. In this paper, we study the ability of the state-of-the-art CRNN approach to learn codes that represent this disruption in homophonic scores. In our experiments, we study the lower bounds in the recognition task of real scores when the models are trained with synthetic data. Two relevant conclusions are drawn: (1) Our serialized ways of encoding the music content are appropriate for CRNN-based OMR; (2) the learning process is possible with synthetic data, but there exists a glass ceiling when recognizing real sheet music.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This paper is part of the I+D+i PID2020-118447RA-I00 (MultiScore) project, funded by MCIN/AEI/10.13039/501100011033. The first author is supported by grant FPU19/04957 from the Spanish Ministerio de Universidades

Few-Shot Symbol Classification via Self-Supervised Learning and Nearest Neighbor

The recognition of symbols within document images is one of the most relevant steps involved in the Document Analysis field. While current state-of-the-art methods based on Deep Learning are capable of adequately performing this task, they generally require a vast amount of data that has to be manually labeled. In this paper, we propose a self-supervised learning-based method that addresses this task by training a neural-based feature extractor with a set of unlabeled documents and performs the recognition task considering just a few reference samples. Experiments on different corpora comprising music, text, and symbol documents report that the proposal is capable of adequately tackling the task with high accuracy rates of up to 95% in few-shot settings. Moreover, results show that the presented strategy outperforms the base supervised learning approaches trained with the same amount of data that, in some cases, even fail to converge. This approach, hence, stands as a lightweight alternative to deal with symbol classification with few annotated data.This paper is part of the project I+D+i PID2020-118447RA-I00 (MultiScore), funded by MCIN/AEI/10.13039/501100011033. The first author is supported by grant FPU19/04957 from the Spanish Ministerio de Universidades. The second and third authors are respectively supported by grants ACIF/2021/356 and APOSTD/2020/256 from “Programa I+D+i de la Generalitat Valenciana”

Late multimodal fusion for image and audio music transcription

Music transcription, which deals with the conversion of music sources into a structured digital format, is a key problem for Music Information Retrieval (MIR). When addressing this challenge in computational terms, the MIR community follows two lines of research: music documents, which is the case of Optical Music Recognition (OMR), or audio recordings, which is the case of Automatic Music Transcription (AMT). The different nature of the aforementioned input data has conditioned these fields to develop modality-specific frameworks. However, their recent definition in terms of sequence labeling tasks leads to a common output representation, which enables research on a combined paradigm. In this respect, multimodal image and audio music transcription comprises the challenge of effectively combining the information conveyed by image and audio modalities. In this work, we explore this question at a late-fusion level: we study four combination approaches in order to merge, for the first time, the hypotheses regarding end-to-end OMR and AMT systems in a lattice-based search space. The results obtained for a series of performance scenarios–in which the corresponding single-modality models yield different error rates–showed interesting benefits of these approaches. In addition, two of the four strategies considered significantly improve the corresponding unimodal standard recognition frameworks.This paper is part of the I+D+i PID2020-118447RA-I00 (MultiScore) project, funded by MCIN/AEI/10.13039/501100011033. Some of the computing resources were provided by the Generalitat Valenciana and the European Union through the FEDER funding programme (IDIFEDER/2020/003). The first and second authors are respectively supported by grants FPU19/04957 from the Spanish Ministerio de Universidades and APOSTD/2020/256 from Generalitat Valenciana

Reconocimiento holístico de partituras musicales

El reconocimiento de patrones con dependencia temporal es común en áreas como el reconocimiento del habla o el procesamiento del lenguaje natural. De manera análoga, encontramos el reconocimiento de texto o video en el campo de análisis de imágenes. Recientemente, las Redes Neuronales Recurrentes (RNN, por sus siglas en inglés) han sido ampliamente utilizadas para resolver estas tareas, arrojando buenos resultados, siguiendo un planteamiento conocido como reconocimiento holístico. Sin embargo, su aplicación en el campo del Reconocimiento Óptico de Música (OMR, por sus siglas en inglés) no es tan sencillo debido a la presencia de diferentes elementos en la misma posición horizontal, interrumpiendo así el flujo lineal temporal. En este artículo se estudia la capacidad de las RNN para aprender códigos que representan esta interrupción en partituras musicales homofónicas. Los resultados obtenidos demuestran que las formas serializadas para codificar el contenido musical propuestas son apropiadas para el OMR basado en RNN y que por tanto, merecen más estudio.Este trabajo cuenta con el apoyo del proyecto del ministerio español HISPAMUS TIN2017-86576-R, parcialmente financiado por la Unión Europea

Decoupling music notation to improve end-to-end Optical Music Recognition

Inspired by the Text Recognition field, end-to-end schemes based on Convolutional Recurrent Neural Networks (CRNN) trained with the Connectionist Temporal Classification (CTC) loss function are considered one of the current state-of-the-art techniques for staff-level Optical Music Recognition (OMR). Unlike text symbols, music-notation elements may be defined as a combination of (i) a shape primitive located in (ii) a certain position in a staff. However, this double nature is generally neglected in the learning process, as each combination is treated as a single token. In this work, we study whether exploiting such particularity of music notation actually benefits the recognition performance and, if so, which approach is the most appropriate. For that, we thoroughly review existing specific approaches that explore this premise and propose different combinations of them. Furthermore, considering the limitations observed in such approaches, a novel decoding strategy specifically designed for OMR is proposed. The results obtained with four different corpora of historical manuscripts show the relevance of leveraging this double nature of music notation since it outperforms the standard approaches where it is ignored. In addition, the proposed decoding leads to significant reductions in the error rates with respect to the other cases.This paper is part of the project I+D+i PID2020-118447RA-I00 (MultiScore), funded by MCIN/AEI/10.13039/501100011033. The first author is supported by grant FPU19/04957 from the Spanish Ministerio de Universidades. The second author is supported by grant ACIF/2021/356 from “Programa I+D+i de la Generalitat Valenciana“. The third author is supported by grant APOSTD/2020/256 from “Programa I+D+i de la Generalitat Valenciana”

Descripción anatómica de la vasculatura arterial carotidea-cerebral en el gallo domestico Gallus Gallus Linnaeus (aves: galliformes: phasianidae)

We describe the carotid-cerebral arterial vasculature of the domestic rooster (Gallus gallus Linnaeus). Ten cocks race Rhode Island of 2.5 kg of weight were used, which were subjected to vascular replesion conservation technique. It was concluded that anastomosis intercarotidea, the formation of the basilar artery and the absence of the vertebral arteries are the most significant components of the cephalic vasculature. It is proposed to standardize the nomenclature of the arteries of the brain-stem carotid arterial because of the confusing terminology used by various authorsSe describe la vasculatura arterial carotídea-cerebral del gallo doméstico (Gallus gallus Linnaeus). Se utilizaron 10 gallos de 2.5 kg de peso, estirpe Rhode Island, los cuales fueron sometidos a la técnica de conservación replesión vascular. Se concluyó que la anastomosis intercarotídea, la formación de la arteria basilar y la ausencia de las arterias vertebrales son los componentes más sobresalientes de la vasculatura cefálica. Se propone estandarizar la nomenclatura de las diversas estructuras anatómicas y vasculares ligadas a la vasculatura arterial carotídea-cerebral ya que son confusas en las diversas publicacione

Collective Effervescence, Self-Transcendence, and Gender Differences in Social Well-Being During 8 March Demonstrations

8 March (8M), now known as International Women’s Day, is a day for feminist claims where demonstrations are organized in over 150 countries, with the participation of millions of women all around the world. These demonstrations can be viewed as collective rituals and thus focus attention on the processes that facilitate different psychosocial effects. This work aims to explore the mechanisms (i.e., behavioral and attentional synchrony, perceived emotional synchrony, and positive and transcendent emotions) involved in participation in the demonstrations of 8 March 2020, collective and ritualized feminist actions, and their correlates associated with personal well-being (i.e., affective well-being and beliefs of personal growth) and collective well-being (i.e., social integration variables: situated identity, solidarity and fusion), collective efficacy and collective growth, and behavioral intention to support the fight for women’s rights. To this end, a cross-cultural study was conducted with the participation of 2,854 people (age 18–79; M = 30.55; SD = 11.66) from countries in Latin America (Mexico, Chile, Argentina, Brazil, Peru, Colombia, and Ecuador) and Europe (Spain and Portugal), with a retrospective correlational cross-sectional design and a convenience sample. Participants were divided between demonstration participants (n = 1,271; 94.0% female) and non-demonstrators or followers who monitored participants through the media and social networks (n = 1,583; 75.87% female). Compared with non-demonstrators and with males, female and non-binary gender respondents had greater scores in mechanisms and criterion variables. Further random-effects model meta-analyses revealed that the perceived emotional synchrony was consistently associated with more proximal mechanisms, as well as with criterion variables. Finally, sequential moderation analyses showed that proposed mechanisms successfully mediated the effects of participation on every criterion variable. These results indicate that participation in 8M marches and demonstrations can be analyzed through the literature on collective rituals. As such, collective participation implies positive outcomes both individually and collectively, which are further reinforced through key psychological mechanisms, in line with a Durkheimian approach to collective rituals.Fil: Zumeta, Larraitz N.. Universidad del País Vasco; EspañaFil: Castro Abril, Pablo. Universidad del País Vasco; EspañaFil: Méndez, Lander. Universidad del País Vasco; EspañaFil: Pizarro, José J.. Universidad del País Vasco; EspañaFil: Włodarczyk, Anna. Universidad Católica del Norte; ChileFil: Basabe, Nekane. Universidad del País Vasco; EspañaFil: Navarro Carrillo, Ginés. Universidad de Jaén; EspañaFil: Padoan De Luca, Sonia. Universidad del País Vasco; EspañaFil: da Costa, Silvia. Universidad del País Vasco; EspañaFil: Alonso Arbiol, Itziar. Universidad del País Vasco; EspañaFil: Torres Gómez, Bárbara. Universidad del País Vasco; EspañaFil: Cakal, Huseyin. Keele University; Reino UnidoFil: Delfino, Gisela Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Pontificia Universidad Católica Argentina "Santa María de los Buenos Aires"; ArgentinaFil: Techio, Elza M.. Universidade Federal da Bahia; BrasilFil: Alzugaray, Carolina. Universidad de Santo Tomas; ChileFil: Bilbao, Marian. Universidad Alberto Hurtado; ChileFil: Villagrán, Loreto. Universidad de Concepción; ChileFil: López López, Wilson. Pontificia Universidad Javeriana; ColombiaFil: Ruiz Pérez, José Ignacio. Universidad Nacional de Colombia; ColombiaFil: Cedeño, Cynthia C.. Universidad Politécnica Salesiana; EcuadorFil: Reyes Valenzuela, Carlos. Universidad Andina Simon Bolivar - Sede Ecuador.; EcuadorFil: Alfaro Beracoechea, Laura. Universidad de Guadalajara; MéxicoFil: Contreras Ibáñez, Carlos César. Universidad Autónoma Metropolitana; MéxicoFil: Ibarra, Manuel Leonardo. Universidad Autónoma del Estado de México; MéxicoFil: Reyes Sosa, Hiram. Universidad Autonoma de Coahuila; MéxicoFil: Cueto, Rosa María. Pontificia Universidad Católica de Perú; PerúFil: Carvalho, Catarina L.. Universidad de Porto; PortugalFil: Pinto, Isabel R.. Universidad de Porto; Portuga

Dietary diversity and nutritional adequacy among an older Spanish population with metabolic syndrome in the PREDIMED-Plus study: a cross-sectional analysis

Dietary guidelines emphasize the importance of a varied diet to provide an adequate nutrient intake. However, an older age is often associated with consumption of monotonous diets that can be nutritionally inadequate, increasing the risk for the development or progression of diet-related chronic diseases, such as metabolic syndrome (MetS). To assess the association between dietary diversity (DD) and nutrient intake adequacy and to identify demographic variables associated with DD, we cross-sectionally analyzed baseline data from the PREDIMED-Plus trial: 6587 Spanish adults aged 55-75 years, with overweight/obesity who also had MetS. An energy-adjusted dietary diversity score (DDS) was calculated using a 143-item validated semi-quantitative food frequency questionnaire (FFQ). Nutrient inadequacy was defined as an intake below 2/3 of the dietary reference intake (DRI) forat least four of 17 nutrients proposed by the Institute of Medicine (IOM). Logistic regression models were used to evaluate the association between DDS and the risk of nutritionally inadequate intakes. In the higher DDS quartile there were more women and less current smokers. Compared with subjects in the highest DDS quartile, those in the lowest DDS quartile had a higher risk of inadequate nutrient intake: odds ratio (OR) = 28.56 (95% confidence interval (CI) 20.80-39.21). When we estimated food varietyfor each of the food groups, participants in the lowest quartile had a higher risk of inadequate nutrient intake for the groups of vegetables, OR = 14.03 (95% CI 10.55-18.65), fruits OR = 11.62 (95% CI 6.81-19.81), dairy products OR = 6.54 (95% CI 4.64-9.22) and protein foods OR = 6.60 (95% CI 1.96-22.24). As DDS decreased, the risk of inadequate nutrients intake rose. Given the impact of nutrient intake adequacy on the prevention of non-communicable diseases, health policies should focus on the promotion of a healthy varied diet, specifically promoting the intake of vegetables and fruit among population groups with lower DDS such as men, smokers or widow(er)s