Computer Music Semantic Processing (PROSEMUS) TIN2006-14932-C02 (original) (raw)

Bridging the Music Semantic Gap

In this paper we present the music information plane and the different levels of information extraction that exist in the musical domain. Based on this approach we propose a way to overcome the existing semantic gap in the music field. Our approximation is twofold: we propose a set of music descriptors that can automatically be extracted from the audio signals, and a top-down approach that adds explicit and formal semantics to these annotations. These music descriptors are generated in two ways: as derivations and combinations of lower-level descriptors and as generalizations induced from manually annotated databases by the intensive application of machine learning. We belive that merging both approaches (bottom-up and top-down) can overcome the existing semantic gap in the musical domain.

Local and global Semantic Networks for the representation of music information

2016

In the field of music informatics, multilayer representation formats are becoming increasingly important, since they enable an integrated and synchronized representation of the various entities that describe a piece of music, from the digital encoding of score symbols to its typographic aspects and audio recordings. Often these formats are based on the eXtensible Markup Language (XML), that allows information embedding, hierarchical structuring and interconnection within a single document. Simultaneously, the advent of the so-called Semantic Web is leading to the transformation of the World Wide Web into an environment where documents are associated with data and metadata. XML is extensively used also in the Semantic Web, since this format supports not only human- but also machine-readable tags. On the one side the Semantic Web aims to create a set of automatically-detectable relationships among data, thus providing users with a number of non-trivial paths to navigate information in...

Content-based music structure analysis with applications to music semantics understanding

Proceedings of the 12th annual ACM international conference on Multimedia - MULTIMEDIA '04, 2004

In this paper, we present a novel approach for music structure analysis. A new segmentation method, beat space segmentation, is proposed and used for music chord detection and vocal/instrumental boundary detection. The wrongly detected chords in the chord pattern sequence and the misclassified vocal/instrumental frames are corrected using heuristics derived from the domain knowledge of music composition. Melody-based similarity regions are detected by matching sub-chord patterns using dynamic programming. The vocal content of the melodybased similarity regions is further analyzed to detect the contentbased similarity regions. Based on melody-based and contentbased similarity regions, the music structure is identified. Experimental results are encouraging and indicate that the performance of the proposed approach is superior to that of the existing methods. We believe that music structure analysis can greatly help music semantics understanding which can aid music transcription, summarization, retrieval and streaming.

09051 Abstracts Collection--Knowledge representation for intelligent music processing}

Abstract From the twenty-fifth to the thirtieth of January, 2009, the Dagstuhl Seminar 09051 on``Knowledge representation for intelligent music processing''was held in Schloss Dagstuhl~--~ Leibniz Centre for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed.

Proceedings of the 3rd Workshop on Learning the Semantics of Audio Signals (LSAS)

Music signals are highly structured data items where different elements combine at various levels of abstraction to create the desired result. This structure is not appropriately taken into account in conventional signal analysis methods, where the overall signal is characterized by calculating straightforward statistical measures in successive time frames. This talk introduces methods for breaking up a complex music signal into its constituent musical elements that have more welldefined "semantic" roles than the entire mixture signal. Methods are discussed for analyzing the vocals and lyrics of music pieces, extracting the melody, the bass line, and chords from music, recognizing musical instruments in complex music, and analyzing the rhythm and sectional form of music. Particular emphasis is placed on novel end-user applications that are enabled by these advanced signal analysis approaches. The applications include new interfaces and techniques for music information retrieval, intelligent music processing tools, and informative music playback interfaces where links to other music pieces are shown at localized segments of the played piece. Techniques for implementing these applications are discussed.

Semantic annotation of digital music

Journal of Computer and System Sciences, 2012

In recent times, digital music items on the internet have been evolving in a vast information space where consumers try to find/locate the piece of music of their choice by means of search engines. The current trend of searching for music by means of music consumers' keywords/tags is unable to provide satisfactory search results. It is argued that search and retrieval of music can be significantly improved provided end-users' tags are associated with semantic information in terms of acoustic metadata-the latter being easy to extract automatically from digital music items. This paper presents a lightweight ontology that will enable music producers to annotate music against MPEG-7 description (with its acoustic metadata) and the generated annotation may in turn be used to deliver meaningful search results. Several potential multimedia ontologies have been explored and a music annotation ontology, named mpeg-7Music, has been designed so that it can be used as a backbone for annotating music items.

Mucosa: A music content semantic annotator

… Information Retrieval, 2005

MUCOSA (Music Content Semantic Annotator) is an environment for the annotation and generation of music metadata at different levels of abstraction. It is composed of three tiers: an annotation client that deals with microannotations (i.e. within-file annotations), a collection tagger, which deals with macro-annotations (i.e. acrossfiles annotations), and a collaborative annotation subsystem, which manages large-scale annotation tasks that can be shared among different research centres. The annotation client is an enhanced version of WaveSurfer, a speech annotation tool. The collection tagger includes tools for automatic generation of unary descriptors, invention of new descriptors, and propagation of descriptors across sub-collections or playlists. Finally, the collaborative annotation subsystem, based on Plone, makes possible to share the annotation chores and results between several research institutions. A collection of annotated songs is available, as a "starter pack" to all the individuals or institutions that are eager to join this initiative.

Semantic Audio Analysis Utilities and Applications

Extraction, representation, organisation and application of metadata about audio recordings are in the concern of semantic audio analysis. Our broad interpretation, aligned with recent developments in the field, includes methodological aspects of semantic audio, such as those related to information management, knowledge representation and applications of the extracted information. In particular, we look at how Semantic Web technologies may be used to enhance information management practices in two audio related areas: music informatics and music production.

Semi-automatic semantic annotation tool for digital music

2011

The Worldwide Web/Internet has changed the music industry by making huge amount of music available to both music publishers and consumers including ordinary listeners or end users. The Web2.0 tagging techniques of music items by artist name, album title, musical style or genre (technically these are termed as syntactic metadata) have given rise to the generation unstructured free form vocabularies. Music search based on these syntactic metadata requires the search query to contain at least one keyword from that vocabulary and it must be an exact match. The semantic Web initiative by W3C proposes machine process-able representation of information but does not stipulate how that can be applied to music items specifically. In this paper we present a novel approach that details a semi-automatic semantic annotation tool to enable music producers to generate music metadata through a mapping between music consumers' free form tags and the acoustic metadata that are automatically extractable from music audio. The proposed annotation tool enables onotology guided annotation process and uses MPEG-7 Audio compliant music annotation ontology represented in dominant semantic web standard OWL 1.0.

The SemanticHIFI project: content-based management and manipulation of musical recordings

Integration of Knowledge, Semantics and Digital …, 2005

The SemanticHIFI project aims at designing and prototyping tomorrow's Hi-fi systems, which will provide music lovers with innovative functions of management and manipulation of musical contents. The limitations of current equipments are mainly related to those of the music distribution media (album-based audio recordings in stereo format), with poor control features and interfaces (album/ track selection, play, stop, volume, etc.). Enabling the manipulation of richer media and related metadata (either distributed with the audio recordings or computed by the user using dedicated indexing tools) opens a wide range of new functionalities: personal indexing and classification of music titles, content-based browsing in personal catalogues, browsing within titles with automatic segmentation and de-mixing tools, 3D audio rendering and assisted mixing features, etc. Moreover, the manipulation of interactive music contents will be made accessible to music consumers, through dedicated performing, and authoring tools. They will then have the possibility of publishing and sharing their personal work with others, through a dedicated peer-to-peer sharing middleware specifically designed for preserving the rights of the used digital media. All these features are the result of the various R&D tasks and experiments performed as part of the project and represent the state-of-the art in various research fields : digital audio signal processing, music information retrieval, man-machine interfaces and peer-to-peer networks. Moreover, the project includes an integration phase, which aims at producing full-featured applications prototypes, designed to fit identified market needs, through technical choices compatible with these markets. This article proposes an overview of the project, by presenting its background and objectives, the main scientific issues and breakthroughs it addresses in relation to the description and extraction of musical information, the main applications features it aims at developing and choices made for their integration into application prototypes compliant with market needs.