Learning, Probability and Logic: Toward a Unified Approach for Content-Based Music Information Retrieval

Within the last 15 years, the field of Music Information Retrieval (MIR) has made tremendous progress in the development of algorithms for organizing and analyzing the ever-increasing large and varied amount of music and music-related data available digitally. However, the development of content-based methods to enable or ameliorate multimedia retrieval still remains a central challenge. In this perspective paper, we critically look at the problem of automatic chord estimation from audio recordings as a case study of content-based algorithms, and point out several bottlenecks in current approaches: expressiveness and flexibility are obtained to the expense of robustness and vice versa; available multimodal sources of information are little exploited; modeling multi-faceted and strongly interrelated musical information is limited with current architectures; models are typically restricted to short-term analysis that does not account for the hierarchical temporal structure of musical signals. Dealing with music data requires the ability to tackle both uncertainty and complex relational structure at multiple levels of representation. Traditional approaches have generally treated these two aspects separately, probability and learning being the usual way to represent uncertainty in knowledge, while logical representation being the usual way to represent knowledge and complex relational information. We advocate that the identified hurdles of current approaches could be overcome by recent developments in the area of Statistical Relational Artificial Intelligence (StarAI) that unifies probability, logic and (deep) learning. We show that existing approaches used in MIR find powerful extensions and unifications in StarAI, and we explain why we think it is time to consider the new perspectives offered by this promising research field

Bias reformulation for one-shot function induction

In recent years predicate invention has been underexplored as a bias reformulation mechanism within Inductive Logic Programming due to difficulties in formulating efficient search mechanisms. However, recent papers on a new approach called Meta-Interpretive Learning have demonstrated that both predicate invention and learning recursive predicates can be efficiently implemented for various fragments of definite clause logic using a form of abduction within a meta-interpreter. This paper explores the effect of bias reformulation produced by Meta-Interpretive Learning on a series of Program Induction tasks involving string transformations. These tasks have real-world applications in the use of spreadsheet technology. The existing implementation of program induction in Microsoft's FlashFill (part of Excel 2013) already has strong performance on this problem, and performs one-shot learning, in which a simple transformation program is generated from a single example instance and applied to the remainder of the column in a spreadsheet. However, no existing technique has been demonstrated to improve learning performance over a series of tasks in the way humans do. In this paper we show how a functional variant of the recently developed MetagolD system can be applied to this task. In experiments we study a regime of layered bias reformulation in which size-bounds of hypotheses are successively relaxed in each layer and learned programs re-use invented predicates from previous layers. Results indicate that this approach leads to consistent speed increases in learning, more compact definitions and consistently higher predictive accuracy over successive layers. Comparison to both FlashFill and human performance indicates that the new system, MetagolDF, has performance approaching the skill level of both an existing commercial system and that of humans on one-shot learning over the same tasks. The induced programs are relatively easily read and understood by a human programmer.National Science Foundation (U.S.) (STC Center for Brains, Minds and Machines Award CCF-1231216

A causal involvement of the left supramarginal gyrus during the retention of musical pitches.

Brain stimulation studies have previously demonstrated a causal link between general pitch memory processes and activity within the left supramarginal gyrus (SMG). Building on this evidence, the present study tested the impact of left SMG stimulation on two distinct pitch memory phases, retention and encoding. Repetitive transcranial magnetic stimulation (rTMS) was employed during the retention stage (Experiment 1) and the encoding phase (Experiment 2) of a pitch recognition task. Stimulation was applied on a trial-by-trial basis over the left SMG (target site) or the vertex (control site). A block without TMS was also completed. In Experiment 1, rTMS over the left SMG during pitch retention led to significantly increased reaction times compared to control conditions. In Experiment 2 no rTMS modulation effects were found during encoding. Experiment 3 was conducted as a control for non-specific stimulation effects; no effects were found when rTMS was applied over the left SMG at the two different time points during a perceptual task. Taken together, these findings highlight a phase-specific involvement of the left SMG in the retention phase of pitch memory, thereby indicating that the left SMG is involved in the maintenance of pitch information

Music, Emotion and Authenticity: A Study of Celtic Music Festival Consumers

This paper centres upon the concept, authenticity, within the context of a Celtic music festival. Increasing attention has been paid to the music-tourism relationship and this paper seeks to elaborate upon the contested meanings and dimensions of Celtic music in the wake of its commodification through tourism. Attention is accorded to the interlocking tensions relating to commodification and authenticity within music and tourism studies and, moreover, the role of emotion within the authenticity and music debate. Drawing upon empirical research conducted at a Celtic music festival (Glasgow, Scotland) comprising in-depth interviews and a questionnaire survey, it is suggested the festival audience attach authenticity to the music on the basis of their emotional interaction with the music. This occurs by the ways in which emotion is evoked within the music and the relationship between music, emotion and audience identities. [ABSTRACT FROM AUTHOR]div_BaM6pub1368pub