Creative professional users musical relevance criteria

Although known item searching for music can be dealt with by searching metadata using existing text search techniques, human subjectivity and variability within the music itself make it very difficult to search for unknown items. This paper examines these problems within the context of text retrieval and music information retrieval. The focus is on ascertaining a relationship between music relevance criteria and those relating to relevance judgements in text retrieval. A data-rich collection of relevance judgements by creative professionals searching for unknown musical items to accompany moving images using real world queries is analysed. The participants in our observations are found to take a socio-cognitive approach and use a range of content and context based criteria. These criteria correlate strongly with those arising from previous text retrieval studies despite the many differences between music and text in their actual content

Audio Content-Based Music Retrieval

The rapidly growing corpus of digital audio material requires novel retrieval strategies for exploring large music collections. Traditional retrieval strategies rely on metadata that describe the actual audio content in words. In the case that such textual descriptions are not available, one requires content-based retrieval strategies which only utilize the raw audio material. In this contribution, we discuss content-based retrieval strategies that follow the query-by-example paradigm: given an audio query, the task is to retrieve all documents that are somehow similar or related to the query from a music collection. Such strategies can be loosely classified according to their "specificity", which refers to the degree of similarity between the query and the database documents. Here, high specificity refers to a strict notion of similarity, whereas low specificity to a rather vague one. Furthermore, we introduce a second classification principle based on "granularity", where one distinguishes between fragment-level and document-level retrieval. Using a classification scheme based on specificity and granularity, we identify various classes of retrieval scenarios, which comprise "audio identification", "audio matching", and "version identification". For these three important classes, we give an overview of representative state-of-the-art approaches, which also illustrate the sometimes subtle but crucial differences between the retrieval scenarios. Finally, we give an outlook on a user-oriented retrieval system, which combines the various retrieval strategies in a unified framework

[[alternative]]Content-Based Music Retrieval

計畫編號：NSC92-2213-E032-021研究期間：200308~200407研究經費：471,000[[sponsorship]]行政院國家科學委員

Content or context? Searching for musical meaning in task-based interactive information retrieval

Creative professionals search for digital music to accompany moving images using interactive information retrieval systems run by music publishers and record companies. This research investigates the creative professionals and the intermediaries communication processes and information seeking and use behaviour with a view to making recommendations to information retrieval systems builders as to the extent of relative importance of content and contextual factors. A communications model is used to suggest that the meaning of music is determined by its listener and use context, as well as cultural codes and competences. The research is framed by a holistic approach based on Ingwersen and Jarvelin’s Interactive Information Seeking, Retrieval and Behavioral processes model

Content-based retrieval of digital music

One of the advantages of having information in digital form is that it lends itself readily to content-based access. This applies to information stored in any media, though content searching through information stored in a structured database or as text is more developed than content searching through information stored in other media such as music In practice, the most common way to index and provide retrieval on digital music is to use its metadata such as title, performer, etc , as has been done in Napster. My research has lead to the development of a digital music information retrieval system called Ceolaire which can index monophonic music files Music files are analysed for notes on the equal tempering scale, where note changes are observed and recorded as being up (U), down (D) or the same (S) relative to the previous note. These note changes are then indexed in a search engine At query time, notes are generated by a user using a web based interface These notes form the query for the retneval engine. A user is presented with a ranked list of highly scored documents. This thesis explores the building and evaluation of the Ceolaire system

Large scale evaluations of multimedia information retrieval: the TRECVid experience

Information Retrieval is a supporting technique which underpins a broad range of content-based applications including retrieval, filtering, summarisation, browsing, classification, clustering, automatic linking, and others. Multimedia information retrieval (MMIR) represents those applications when applied to multimedia information such as image, video, music, etc. In this presentation and extended abstract we are primarily concerned with MMIR as applied to information in digital video format. We begin with a brief overview of large scale evaluations of IR tasks in areas such as text, image and music, just to illustrate that this phenomenon is not just restricted to MMIR on video. The main contribution, however, is a set of pointers and a summarisation of the work done as part of TRECVid, the annual benchmarking exercise for video retrieval tasks

Content Based Retrieval and Navigation of Music

Contents 1 Introduction ................................................... 3 2 Literature Review .............................................. 4 2.1 Navigation ............................................... 4 2.2 Navigation of audio ........................................ 4 2.3 Contentrepresentations ..................................... 5 2.3.1 The musical score ................................... 6 2.3.2 Performance data .................................... 6 2.3.3 Musical pitch contours ................................ 6 2.3.4 Alternative representations ............................ 7 2.3.5 The Fourier transform ................................ 7 2.4 Content based retrieval ..................................... 8 2.4.1 Retrieval of digital audio samples ....................... 8 2.4.2 Query by humming .................................. 8 2.4.3 Lemstrm and Laine ................................. 9 2.4.4 Image matching techni

Music information retrieval: conceptuel framework, annotation and user behaviour

Understanding music is a process both based on and influenced by the knowledge and experience of the listener. Although content-based music retrieval has been given increasing attention in recent years, much of the research still focuses on bottom-up retrieval techniques. In order to make a music information retrieval system appealing and useful to the user, more effort should be spent on constructing systems that both operate directly on the encoding of the physical energy of music and are flexible with respect to users’ experiences. This thesis is based on a user-centred approach, taking into account the mutual relationship between music as an acoustic phenomenon and as an expressive phenomenon. The issues it addresses are: the lack of a conceptual framework, the shortage of annotated musical audio databases, the lack of understanding of the behaviour of system users and shortage of user-dependent knowledge with respect to high-level features of music. In the theoretical part of this thesis, a conceptual framework for content-based music information retrieval is defined. The proposed conceptual framework - the first of its kind - is conceived as a coordinating structure between the automatic description of low-level music content, and the description of high-level content by the system users. A general framework for the manual annotation of musical audio is outlined as well. A new methodology for the manual annotation of musical audio is introduced and tested in case studies. The results from these studies show that manually annotated music files can be of great help in the development of accurate analysis tools for music information retrieval. Empirical investigation is the foundation on which the aforementioned theoretical framework is built. Two elaborate studies involving different experimental issues are presented. In the first study, elements of signification related to spontaneous user behaviour are clarified. In the second study, a global profile of music information retrieval system users is given and their description of high-level content is discussed. This study has uncovered relationships between the users’ demographical background and their perception of expressive and structural features of music. Such a multi-level approach is exceptional as it included a large sample of the population of real users of interactive music systems. Tests have shown that the findings of this study are representative of the targeted population. Finally, the multi-purpose material provided by the theoretical background and the results from empirical investigations are put into practice in three music information retrieval applications: a prototype of a user interface based on a taxonomy, an annotated database of experimental findings and a prototype semantic user recommender system. Results are presented and discussed for all methods used. They show that, if reliably generated, the use of knowledge on users can significantly improve the quality of music content analysis. This thesis demonstrates that an informed knowledge of human approaches to music information retrieval provides valuable insights, which may be of particular assistance in the development of user-friendly, content-based access to digital music collections

A Concept for Using Combined Multimodal Queries in Digital Music Libraries

Περιέχει το πλήρες κείμενοIn this paper, we propose a concept for using combined multimodal queries in the context of digital music libraries. Whereas usual mechanisms for content-based music retrieval only consider a single query mode, such as query-by-humming, full-text lyrics-search or query-by-example using short audio snippets, our proposed concept allows to combine those different modalities into one integrated query. Our particular contributions consist of concepts for query formulation, combined content-based retrieval and presentation of a suitably ranked result list. The proposed concepts have been realized within the context of the PROBADO Music Repository and allow for music retrieval based on combining full-text lyrics search and score-based query-by-example search