1,783 research outputs found
Robust Tuning Datasets for Statistical Machine Translation
We explore the idea of automatically crafting a tuning dataset for
Statistical Machine Translation (SMT) that makes the hyper-parameters of the
SMT system more robust with respect to some specific deficiencies of the
parameter tuning algorithms. This is an under-explored research direction,
which can allow better parameter tuning. In this paper, we achieve this goal by
selecting a subset of the available sentence pairs, which are more suitable for
specific combinations of optimizers, objective functions, and evaluation
measures. We demonstrate the potential of the idea with the pairwise ranking
optimization (PRO) optimizer, which is known to yield too short translations.
We show that the learning problem can be alleviated by tuning on a subset of
the development set, selected based on sentence length. In particular, using
the longest 50% of the tuning sentences, we achieve two-fold tuning speedup,
and improvements in BLEU score that rival those of alternatives, which fix
BLEU+1's smoothing instead.Comment: RANLP-201
Cortical Representation Underlying the Semantic Processing of Numerical Symbols: Evidence from Adult and Developmental Studies
Humans possess the remarkable ability to process numerical information using numerical symbols such as Arabic digits. A growing body of neuroimaging work has provided new insights into the neural correlates associated with symbolic numerical magnitude processing. However, little is known about the cortical specialization underlying the representation of symbolic numerical magnitude in adults and children. To constrain our current knowledge, I conducted a series of functional Magnetic Resonance Imaging (fMRI) studies that aimed to better understand the functional specialization of symbolic numerical magnitudes representation in the human brain.
Using a number line estimation task, the first study contrasted the brain activation associated with processing symbolic numerical magnitude against the brain activation associated with non-numerical magnitude (brightness) processing. Results demonstrated a right lateralized parietal network that was commonly engaged when magnitude dimensions were processed. However, the left intraparietal sulcus (IPS) was additionally activated when symbolic numerical magnitudes were estimated, suggesting that number is a special category amongst magnitude dimensions and that the left hemisphere plays a critical role in representing number.
The second study tested a child friendly version of an fMRI-adaptation paradigm in adults. For this participantâs brain response was habituated to a numerical value (i.e., 6) and signal recovery in response to the presentation of numerical deviants was investigated. Across two different brain normalization procedures results showed a replication of previous findings demonstrating that the brain response of the IPS is modulated by the semantic meaning of numbers in the absence of overt response selection.
The last study aimed to unravel developmental changes in the cortical representation of symbolic numerical magnitudes in children. Using the paradigm tested in chapter 2, results demonstrated an increase in the signal recovery with age in the left IPS as well as an age-independent signal recovery in the right IPS. This finding indicates that the left IPS becomes increasingly specialized for the representation of symbolic numerical magnitudes over developmental time, while the right IPS may play a different and earlier role in symbolic numerical magnitude representation.
Findings of these studies are discussed in relation to our current knowledge about symbolic numerical magnitude representation
Speech Recognition Challenge in the Wild: Arabic MGB-3
This paper describes the Arabic MGB-3 Challenge - Arabic Speech Recognition
in the Wild. Unlike last year's Arabic MGB-2 Challenge, for which the
recognition task was based on more than 1,200 hours broadcast TV news
recordings from Aljazeera Arabic TV programs, MGB-3 emphasises dialectal Arabic
using a multi-genre collection of Egyptian YouTube videos. Seven genres were
used for the data collection: comedy, cooking, family/kids, fashion, drama,
sports, and science (TEDx). A total of 16 hours of videos, split evenly across
the different genres, were divided into adaptation, development and evaluation
data sets. The Arabic MGB-Challenge comprised two tasks: A) Speech
transcription, evaluated on the MGB-3 test set, along with the 10 hour MGB-2
test set to report progress on the MGB-2 evaluation; B) Arabic dialect
identification, introduced this year in order to distinguish between four major
Arabic dialects - Egyptian, Levantine, North African, Gulf, as well as Modern
Standard Arabic. Two hours of audio per dialect were released for development
and a further two hours were used for evaluation. For dialect identification,
both lexical features and i-vector bottleneck features were shared with
participants in addition to the raw audio recordings. Overall, thirteen teams
submitted ten systems to the challenge. We outline the approaches adopted in
each system, and summarise the evaluation results
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Many applications of AI involve scoring individuals using a learned function
of their attributes. These predictive risk scores are then used to take
decisions based on whether the score exceeds a certain threshold, which may
vary depending on the context. The level of delegation granted to such systems
in critical applications like credit lending and medical diagnosis will heavily
depend on how questions of fairness can be answered. In this paper, we study
fairness for the problem of learning scoring functions from binary labeled
data, a classic learning task known as bipartite ranking. We argue that the
functional nature of the ROC curve, the gold standard measure of ranking
accuracy in this context, leads to several ways of formulating fairness
constraints. We introduce general families of fairness definitions based on the
AUC and on ROC curves, and show that our ROC-based constraints can be
instantiated such that classifiers obtained by thresholding the scoring
function satisfy classification fairness for a desired range of thresholds. We
establish generalization bounds for scoring functions learned under such
constraints, design practical learning algorithms and show the relevance our
approach with numerical experiments on real and synthetic data.Comment: 35 pages, 13 figures, 6 table
Developmental specialization of the left parietal cortex for the semantic representation of Arabic numerals: an fMR-adaptation study
The way the human brain constructs representations of numerical symbols is poorly understood. While increasing evidence from neuroimaging studies has indicated that the intraparietal sulcus (IPS) becomes increasingly specialized for symbolic numerical magnitude representation over developmental time, the extent to which these changes are associated with age-related differences in symbolic numerical magnitude representation or with developmental changes in non-numerical processes, such as response selection, remains to be uncovered. To address these outstanding questions we investigated developmental changes in the cortical representation of symbolic numerical magnitude in 6- to 14-year-old children using a passive functional magnetic resonance imaging adaptation design, thereby mitigating the influence of response selection. A single-digit Arabic numeral was repeatedly presented on a computer screen and interspersed with the presentation of novel digits deviating as a function of numerical ratio (smaller/larger number). Results demonstrated a correlation between age and numerical ratio in the left IPS, suggesting an age-related increase in the extent to which numerical symbols are represented in the left IPS. Brain activation of the right IPS was modulated by numerical ratio but did not correlate with age, indicating hemispheric differences in IPS engagement during the development of symbolic numerical representation
Multicultural coping: Chinese-Canadian adolescents, male gender role conflict, and psychological distress
One hundred seventy-nine Chinese Canadian adolescents completed measures of male gender role conflict, culturally specific coping strategies, and psychological distress. Structural equation results demonstrate that Avoidance Coping and Engagement Coping mediated the relationship between all aspects of male gender role conflict, with the exception of Restricted Affectionate Behavior Between Men and psychological distress. Implications for counseling practice, further research, and the psychology of men are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved
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