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Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior
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In: Sustainability; Volume 14; Issue 8; Pages: 4799 (2022)
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Lexicon‐pointed hybrid N‐gram Features Extraction Model (LeNFEM) for sentence level sentiment analysis
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Prosody-Based Measures for Automatic Severity Assessment of Dysarthric Speech
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In: Applied Sciences; Volume 10; Issue 19; Pages: 6999 (2020)
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Automatic Irony Detection using Feature Fusion and Ensemble Classifier
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Using deep learning methods for supervised speech enhancement in noisy and reverberant environments
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Mutual information estimation and its applications to machine learning ...
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Gao, Shuyang. - : University of Southern California Digital Library (USC.DL), 2018
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Necessary Morphological Patches Extraction for Automatic Micro-Expression Recognition
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In: Applied Sciences ; Volume 8 ; Issue 10 (2018)
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Presenting a Labelled Dataset for Real-Time Detection of Abusive User Posts
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In: Conference papers (2017)
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Improving TTS with corpus-specific pronunciation adaptation
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In: Interspeech ; https://hal.inria.fr/hal-01338111 ; Interspeech, Sep 2016, San Francisco, United States (2016)
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Understanding behavioral differences between short and long-term drinking abstainers from social media
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Abstract:
Drinking alcohol has high cost on society. The journey from being a regular drinker to a successful quitter may be a long and hard journey, fraught with the risk to relapse. Research has shown that certain behavioral changes can be effective towards staying abstained. Traditional way to conduct research on drinking abstainers uses questionnaire based approach to collect data from a curated group of people. However, it is an expensive approach in both cost and time and often results in small data with less diversity. Recently, social media has emerged as a rich data source. Reddit is one such social media platform that has a community (‘subreddit’) with an interest to quit drinking. The discussions among the group dates back to year 2011 and contain more than 40,000 posts. This large scale data is generated by users themselves and without being limited by any survey questionnaires. The most predictive factors from the features (unigrams, topics and LIWC) associated with short-term and long-term abstinence are identified using Lasso. It is seen that many common patterns manifest in unigrams, topics and LIWC. Whilst topics provided much richer associations between a group of words and the outcome, unigrams and LIWC are found to be good at finding highly predictive solo and psycho linguistically important words. Combining them we have found that many interesting patterns that are associated with the successful attempt made by the long-term abstainer, at the same time finding many of the common issues faced during the initial period of abstinence.
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Keyword:
abstinence; feature selection; health promotion; Reddit; stop drinking
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URL: http://hdl.handle.net/10536/DRO/DU:30093593
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Coronary artery analysis: Computerâ assisted selection of bestâ quality segments in multipleâ phase coronary CT angiography
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Probabilistic Speaker Pronunciation Adaptation for Spontaneous Speech Synthesis Using Linguistic Features
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In: Proceedings of Statistical Language and Speech Processing ; International Conference on Statistical Language and Speech Processing (SLSP) ; https://hal.inria.fr/hal-01181192 ; International Conference on Statistical Language and Speech Processing (SLSP), Nov 2015, Budapest, Hungary. pp.229-241 (2015)
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Classification Of Political Affiliations By Reduced Number Of Features ...
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Classification Of Political Affiliations By Reduced Number Of Features ...
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A Novel Real-Time Speech Summarizer System for the Learning of Sustainability
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In: Sustainability ; Volume 7 ; Issue 4 ; Pages 3885-3899 (2015)
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Models for predicting the inflectional paradigm of Croatian words
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In: Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, Vol 1, Iss 2, Pp 1-34 (2013) (2013)
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Perceptually motivated speech recognition and mispronunciation detection
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Whodunnit ? Searching for the Most Important Feature Types Signalling Emotion-Related User States in Speech
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: Elsevier, 2012
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Multilingual Vandalism Detection Using Language-Independent & Ex Post Facto Evidence
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In: Departmental Papers (CIS) (2011)
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