Automatic Semantic Annotation of Music with Harmonic Structure

This paper presents an annotation model for harmonic structure of a piece of music, and a rule system that supports the automatic generation of harmonic annotations. Musical structure has so far received relatively little attention in the context of musical metadata and annotation, although it is highly relevant for musicians, musicologists and indirectly for music listeners. Activities in semantic annotation of music have so far mostly concentrated on features derived from audio data and file-level metadata. We have implemented a model and rule system for harmonic annotation as a starting point for semantic annotation of musical structure. Our model is for the musical style of Jazz, but the approach is not restricted to this style. The rule system describes a grammar that allows the fully automatic creation of an harmonic analysis as tree-structured annotations. We present a prototype ontology that defines the layers of harmonic analysis from chords symbols to the level of a complete piece. The annotation can be made on music in various formats, provided there is a way of addressing either chords or time points within the music. We argue that this approach, in connection with manual annotation, can support a number of application scenarios in music production, education, and retrieval and in musicology

The Synonym management process in SAREL

The specification phase is one of the most important and least supported parts of the software development process. The SAREL system has been conceived as a knowledge-based tool to improve the specification phase. The purpose of SAREL (Assistance System for Writing Software Specifications in Natural Language) is to assist engineers in the creation of software specifications written in Natural Language (NL). These documents are divided into several parts. We can distinguish the Introduction and the Overall Description as parts that should be used in the Knowledge Base construction. The information contained in the Specific Requirements Section corresponds to the information represented in the Requirements Base. In order to obtain high-quality software requirements specification the writing norms that define the linguistic restrictions required and the software engineering constraints related to the quality factors have been taken into account. One of the controls performed is the lexical analysis that verifies the words belong to the application domain lexicon which consists of the Required and the Extended lexicon. In this sense a synonym management process is needed in order to get a quality software specification. The aim of this paper is to present the synonym management process performed during the Knowledge Base construction. Such process makes use of the Spanish Wordnet developed inside the Eurowordnet project. This process generates both the Required lexicon and the Extended lexicon that will be used during the Requirements Base construction.Postprint (published version

PARASOL: Parametric Style Control for Diffusion Image Synthesis

We propose PARASOL, a multi-modal synthesis model that enables disentangled, parametric control of the visual style of the image by jointly conditioning synthesis on both content and a fine-grained visual style embedding. We train a latent diffusion model (LDM) using specific losses for each modality and adapt the classifier-free guidance for encouraging disentangled control over independent content and style modalities at inference time. We leverage auxiliary semantic and style-based search to create training triplets for supervision of the LDM, ensuring complementarity of content and style cues. PARASOL shows promise for enabling nuanced control over visual style in diffusion models for image creation and stylization, as well as generative search where text-based search results may be adapted to more closely match user intent by interpolating both content and style descriptors.Comment: Added Appendi

Limits of Kansei – Kansei unlimited

This article discusses momentary limitations of the Kansei Engineering methods. There are for example the focus on the evaluation of colour and form factors, as well as the highly time consuming creation of the questionnaires. To overcome these limits we firstly suggest the integration of word lists from related research fields, like sociology and cognitive psychology on product emotions in the Kansei questionnaires. Thereafter we present a study on the wide range of Kansei attributes treated in an industrial setting. Concept words used by designers are being collected through word maps and categorized into attributes. In a third step we introduce a user-product interaction schema in which the Kansei attributes from the study are positioned. This schema unfolds potential expansion points for future applications of Kansei engineering beyond its current limits

Using NLP tools in the specification phase

The software quality control is one of the main topics in the Software Engineering area. To put the effort in the quality control during the specification phase leads us to detect possible mistakes in an early steps and, easily, to correct them before the design and implementation steps start. In this framework the goal of SAREL system, a knowledge-based system, is twofold. On one hand, to help software engineers in the creation of quality Software Requirements Specifications. On the other hand, to analyze the correspondence between two different conceptual representations associated with two different Software Requirements Specification documents. For the first goal, a set of NLP and Knowledge management tools is applied to obtain a conceptual representation that can be validated and managed by the software engineer. For the second goal we have established some correspondence measures in order to get a comparison between two conceptual representations. This information will be useful during the interaction.Postprint (published version

Doc2RDFa: Semantic Annotation for Web Documents

Ever since its conception, the amount of data published on the worldwide web has been rapidly growing to the point where it has become an important source of both general and domain specific information. However, the majority of documents published online are not machine readable by default. Many researchers believe that the answer to this problem is to semantically annotate these documents, and thereby contribute to the linked "Web of Data". Yet, the process of annotating web documents remains an open challenge. While some efforts towards simplifying this process have been made in the recent years, there is still a lack of semantic content creation tools that integrate well with information worker toolsets. Towards this end, we introduce Doc2RDFa, an HTML rich text processor with the ability to automatically and manually annotate domain-specific Content