Search results for " Classification"
showing 10 items of 1043 documents
Multitask deep learning for native language identification
2020
Identifying the native language of a person by their text written in English (L1 identification) plays an important role in such tasks as authorship profiling and identification. With the current proliferation of misinformation in social media, these methods are especially topical. Most studies in this field have focused on the development of supervised classification algorithms, that are trained on a single L1 dataset. Although multiple labeled datasets are available for L1 identification, they contain texts authored by speakers of different languages and do not completely overlap. Current approaches achieve high accuracy on available datasets, but this is attained by training an individua…
Glottal Source Features for Automatic Speech-Based Depression Assessment
2017
Depression is one of the most prominent mental disorders, with an increasing rate that makes it the fourth cause of disability worldwide. The field of automated depression assessment has emerged to aid clinicians in the form of a decision support system. Such a system could assist as a pre-screening tool, or even for monitoring high risk populations. Related work most commonly involves multimodal approaches, typically combining audio and visual signals to identify depression presence and/or severity. The current study explores categorical assessment of depression using audio features alone. Specifically, since depression-related vocal characteristics impact the glottal source signal, we exa…
Testing a spectral-based feature set for audio genre classification
2011
Automatic musical genre classification is an important information retrieval task since it can be applied for practical purposes such as the organization of data collections in the digital music industry. However, this task remains an open question because the current state of the art shows far from satisfactory outcomes in terms of classification performance. Moreover, the most common algorithms that are used for this task are not designed for modelling music perception. This study suggests a framework for testing different musical features for use in music genre classification and evaluates the performance of this task based on two musical descriptors. The focus of this study is on automa…
Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance
2022
Accurate sleep stage classification is vital to assess sleep quality and diagnose sleep disorders. Numerous deep learning based models have been designed for accomplishing this labor automatically. However, the class imbalance problem existing in polysomnography (PSG) datasets has been barely investigated in previous studies, which is one of the most challenging obstacles for the real-world sleep staging application. To address this issue, this paper proposes novel methods with signal-driven and image-driven ways of noise addition to balance the imbalanced relationship in the training dataset samples. We evaluate the effectiveness of the proposed methods which are integrated into a convolut…
Triacylglycerol Analysis in Human Milk and Other Mammalian Species: Small-Scale Sample Preparation, Characterization, and Statistical Classification …
2015
In this work, a method for the separation of triacylglycerols (TAGs) present in human milk and from other mammalian species by reversed-phase high-performance liquid chromatography using a core–shell particle packed column with UV and evaporative light-scattering detectors is described. Under optimal conditions, a mobile phase containing acetonitrile/n-pentanol at 10 °C gave an excellent resolution among more than 50 TAG peaks. A small-scale method for fat extraction in these milks (particularly of interest for human milk samples) using minimal amounts of sample and reagents was also developed. The proposed extraction protocol and the traditional method were compared, giving similar results…
Toddlers’ understanding of basic emotions: identification, labeling and causality / La comprensión temprana de las emociones básicas: identificación,…
2014
AbstractThe aim of this paper is to explore the early acquisition pattern of the understanding of basic emotions. Many studies indicate that three-year-old children identify emotions such as joy or sadness, but it is not known how this knowledge arises. Fifty-seven boys and girls between 21 and 32 months were assessed using the Brunet-Lezine-R developmental scale (BL-R) (Josse, 1997) and the Affective knowledge Test (AKT) (Denham, 1986). Through this test we evaluated the children’s knowledge of four basic emotions (happiness, sadness, anger and fear) in three of its components (identification, causality and linguistic labeling). In order to track knowledge acquisition longitudinally, a sma…
Measuring music-induced emotion: A comparison of emotion models, personality biases, and intensity of experiences
2011
Most previous studies investigating music-induced emotions have applied emotion models developed in other fields to the domain of music. The aim of this study was to compare the applicability of music-specific and general emotion models – namely the Geneva Emotional Music Scale (GEMS), and the discrete and dimensional emotion models – in the assessment of music-induced emotions. A related aim was to explore the role of individual difference variables (such as personality and mood) in music-induced emotions, and to discover whether some emotion models reflect these individual differences more strongly than others. One hundred and forty-eight participants listened to 16 film music excerpts a…
A functional MRI study of happy and sad emotions in music with and without lyrics
2011
Musical emotions, such as happiness and sadness, have been investigated using instrumental music devoid of linguistic content. However, pop and rock, the most common musical genres, utilize lyrics for conveying emotions. Using participants’ self-selected musical excerpts, we studied their behavior and brain responses to elucidate how lyrics interact with musical emotion processing, as reflected by emotion recognition and activation of limbic areas involved in affective experience. We extracted samples from subjects’ selections of sad and happy pieces and sorted them according to the presence of lyrics. Acoustic feature analysis showed that music with lyrics differed from music without lyric…
Fifty shades of blue : Classification of music-evoked sadness
2016
It has been repeatedly shown that sad music induces mainly pleasant or mixed emotions, and is particularly relevant for self-regulation goals. However, this is not entirely compatible with the view that sadness is one of the basic emotions experienced in the face of an unpleasant event or a loss. Also, a distinction between grief and sadness is often drawn, which seemingly does not have relevance in relation to musical experiences. The discrepancy between the positive accounts of emotions associated with sad music and those present in ordinary sadness may be related to the previously unacknowledged spectrum of affects associated with music-related sadness. The present study aims to expose t…
Automated approach for indirect immunofluorescence images classification based on unsupervised clustering method
2018
Autoimmune diseases (ADs) are a collection of many complex disorders of unknown aetiology resulting in immune responses to self-antigens and are thought to result from interactions between genetic and environmental factors. ADs collectively are amongst the most prevalent diseases in the U.S., affecting at least 7% of the population. The diagnosis of ADs is very complex, the standard screening methods provides seeking and recognizing of Antinuclear Antibodies (ANA) by Indirect ImmunoFluorescence (IIF) based on HEp-2 cells. In this paper an automatic system able to identify and classify the Centromere pattern is presented. The method is based on the grouping of centromeres present on the cell…