Search results for " information retrieval"
showing 10 items of 80 documents
Tempo Induction from Music Recordings Using Ensemble Empirical Mode Decomposition Analysis
2011
Tempo and beat are among the most important features of Western music. Owing to the perceptual nature of tempo, its automatic analysis and extraction remains a difficult task for a large variety of music genres. Western music notation represents musical events using a hierarchical metrical structure distinguishing different time scales. This hierarchy is often modeled using three levels: the tatum, the tactus, and the measure. The tatum represents the shortest durational value in music that is not just an accidental phenomenon (Bilmes 1993). The tactus period is the most perceptually prominent period, and is the period at which most humans would tap their feet in time with the music (Lerdah…
Non-speech voice for sonic interaction: a catalogue
2016
This paper surveys the uses of non-speech voice as an interaction modality within sonic applications. Three main contexts of use have been identified: sound retrieval, sound synthesis and control, and sound design. An overview of different choices and techniques regarding the style of interaction, the selection of vocal features and their mapping to sound features or controls is here displayed. A comprehensive collection of examples instantiates the use of non-speech voice in actual tools for sonic interaction. It is pointed out that while voice-based techniques are already being used proficiently in sound retrieval and sound synthesis, their use in sound design is still at an exploratory p…
Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening
2020
Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that co…
Distributed Real-Time Sentiment Analysis for Big Data Social Streams
2014
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about "what-is-happening-now" with a negligible delay. The real challenge with real-time stream data processing is that it is impossible to store instances of data, and therefore online analytical algorithms are utilized. To perform real-time analytics, pre-processing of data should be performed in a way that only a short summary of stream is stored in main memory. In addition, due to high speed of arrival, average processing time for each instance of data should be in such a way that…
Managing the flow of private information on children and parents in poverty situations : Creating a panoptic eye in interorganizational networks?
2018
In this article, we discuss how the flow of private information about children and families in poverty situations is managed in interorganizational networks that aim to combat child poverty. Although practices for sharing information and documentation between child and family social work services are highly encouraged and recommended to create supportive features for parents and children, this development often results in undesirable forms of governmentality. Interorganizational networking also creates controlling side effects because the exchange of information in networks of child and family services may wield a holistic power over families. We theorize this issue by using the Foucauldian…
The welfare cost of unpriced heterogeneity in insurance markets
2016
We consider the welfare loss of unpriced heterogeneity in insurance markets, which results when private information or regulatory constraints prevent insurance companies to set premiums reflecting expected costs. We propose a methodology which uses survey data to measure this welfare loss. After identifying some “types” which determine expected risk and insurance demand, we derive the key factors defining the demand and cost functions in each market induced by these unobservable types. These are used to quantify the efficiency costs of unpriced heterogeneity. We apply our methods to the US Long-Term Care and Medigap insurance markets, where we find that unpriced heterogeneity causes substan…
On the social value of publicly disclosed information and environmental regulation
2018
Abstract This paper presents an analysis of environmental policy in imperfectly competitive market with publicly disclosed and privately-held information about costs. We examine the potential asymmetry-reducing role of disclosure and its impact on setting environmental taxes. From a policy perspective, our findings show that disclosure with verifiable reports, is a valuable public good, provides greater transparency in the market, and is generally efficiency enhancing. Results suggest that access to publicly disclosed information enables the fine-tuning of the tax rules towards specific environmental circumstances and improves the ability of the regulator to levy firm-specific environmental…
Entry and espionage with noisy signals
2014
Abstract We analyze the effect of industrial espionage on entry deterrence. We consider a monopoly incumbent who may expand capacity to deter entry, and a potential entrant who owns an Intelligence System. The Intelligence System (IS) generates a noisy signal based on the incumbentʼs actions. The potential entrant uses this signal to decide whether or not to enter the market. The incumbent may signal-jam to manipulate the likelihood of the noisy signals and hence affect the entrantʼs decisions. If the precision of the IS is commonly known, the incumbent benefits from his rivalʼs espionage. Actually, he benefits more the higher is the precision of the IS while the spying entrant is worse off…
Exploring relationships between audio features and emotion in music
2009
In this paper, we present an analysis of the associations between emotion categories and audio features automatically extracted from raw audio data. This work is based on 110 excerpts from film soundtracks evaluated by 116 listeners. This data is annotated with 5 basic emotions (fear, anger, happiness, sadness, tenderness) on a 7 points scale. Exploiting state-of-the-art Music Information Retrieval (MIR) techniques, we extract audio features of different kind: timbral, rhythmic and tonal. Among others we also compute estimations of dissonance, mode, onset rate and loudness. We study statistical relations between audio descriptors and emotion categories confirming results from psychological …
Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation
2016
This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…