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In the last years, several approaches have addressed the encoding of the different music scripts used for plainchant. One of these approaches is the GABC format. While being a comprehensive symbolic representation of square notation, the lack of a ...

The loss of many high-street music venues in recent years has highlighted their connectedness to place and communities. Understanding the emotional geographies of these venues, as experienced by their patrons, is key to explaining the outcry that can ...

Musical form is defined as the overall structure of a music piece. The labelling of musical form types (for the purpose of, e.g., querying online music databases) by utilizing raw audio alone is a relatively unexplored area in the field of music ...

In 2021, the RISM Digital Center introduced RISM Online. This represented a shift in how we present the RISM data to a global audience, supporting new methods of digital research and keeping the RISM project central to modern music scholarship. RISM ...

A guitar tuning is the allocation of pitches to the open strings of the guitar. A wide variety of guitar tunings are featured in genres such as blues, classical, folk, and rock. Standard tuning provides a convenient placing of intervals and a manageable ...

The paper describes an online tool, OMRAT, for semi-automatic annotation of music scores for Optical Music Recognition (OMR) systems. OMRAT uses deep neural networks, machine learning, and music notation ontologies at different stages to respectively ...

Nowadays, visual data (image, videos, and feature vectors) is generated in many applications, such as surveillance or automated retail stores. The fast rate of accumulating such visual data makes the task of analyzing it or getting insights a tedious ...

AsaPy is a custom-made Python library designed to simplify and optimize the analysis of aerospace simulation data. Instead of introducing new methodologies, it excels in combining various established techniques, creating a unified, specialized platform. ...

The evolution of conversational agents, in particular the case with chatbots, has experienced huge boosts in recent years, enabling a variety of tasks and allowing users to enjoy much more interaction. This research presents a sequential model for a ...

With the rapid advances in deep learning, we have witnessed a strongly increased interest in conversational recommender systems (CRS). Until recently, however, even the latest generative models exhibited major limitations and they frequently return non-...

In recommender systems, the presentation of explanations plays a crucial role in supporting users’ decision-making processes. Although numerous existing studies have focused on the effects (e.g., transparency) of explanation content, explanation ...

Recommender Systems have played an important role in our daily lives for many years. However, it is only recently that their social impact has raised ethical issues and has thus been considered in the design of such systems. Particularly, News ...

Conversational Recommender Systems (CRS) have recently drawn attention due to their capacity of delivering personalized recommendations through multi-turn natural language interactions. In this paper, we fit into this research line and we introduce a ...

Music recommender systems play a pivotal role in catering to diverse user preferences and fostering personalized listening experiences. At the same time, sentiments can profoundly influence music by shaping its emotional expression and evoking specific ...

In news media, recommender system technology faces several domain-specific challenges. The continuous stream of new content and users deems content-based recommendation strategies, based on similar-item retrieval, to remain popular. However, a ...

When using web search engines to conduct inquiries on debated topics, searchers’ interactions with search results are commonly affected by a combination of searcher and system biases. While prior work has mainly investigated these biases in isolation, ...

The research community has become increasingly aware of possible undesired effects of algorithmic biases in recommender systems. One common bias in such systems is to over-proportionally expose certain items to users, which may ultimately result in a ...

Context has been an important topic in recommender systems over the past two decades. Most of the prior CARS papers manually selected and considered only a few crucial contextual variables in an application, such as time, location, and company of a ...

In the context of recommender systems (RS), the concept of diversity is probably the most studied perspective beyond mere accuracy. Despite the extensive development of diversity measures and enhancement methods, the understanding of how users perceive ...

Next-item recommender systems are often trained using only positive feedback with randomly-sampled negative feedback. We show the benefits of using real negative feedback both as inputs into the user sequence and also as negative targets for training a ...