Articles

In this paper, the most recent Sharif University of Technology (SUT) speaker recognition system devel- oped for NIST 2016 Speaker Recognition Evaluation (SRE) is described. The major challenge in this evaluation is the language mismatch between training and evaluation data. The submission is related to the fixed condition of NIST …...

Reliability of Automatic Speaker Verification (ASV) systems has always been a concern in dealing with spoofing attacks. Among these attacks, replay attack is the simplest and the easiest accessible method. This paper describes a replay spoofing detection system applied to ASVspoof2017 corpus. To reach this goal, features such as Constant-Q …...

. Valence shifters are complex linguistic structures that can modify the sentiment orientations of texts. In this paper, the authors concentrate on the study of shifters in Vietnamese texts and a discussion on the distribution of different types of shifters in the hotel reviews is presented. Finally, an approach for …...

A tone group parser could be one of the most important components of the Taiwanese text-to-speech system. In this paper, we offered the hypothesis of tonal government to emphasis the idea that if the allotone selection can be made for each word in a sentence then the tone groups will …...

We improved sentiment classifier for predicting document-level sentiments from Twitter by using multi-channel lexicon embedidngs. The core of the architecture is based on CNN- BiLSTM that can capture high level features and long term dependency in documents. We also applied multi-channel method on lexicon to improve lexicon features. The macro- …...

This paper tried to amplify a sense of emotion toward drama. Using Long Short-Term Memory Recurrent Neural Network to model and predict dynamic emotion(Arousal and Valence) recognition. After building model, we transplant whole framework and take results from it on visualizing. We have two demo version: RGB version and Vignette …...

Under the issue of gender and Natural Language Processing (NLP), most papers aim at gender- norm language that spoken by biologically males and females with opposite-sex desires. However, from the point of view of sexual orientation, this study presents the first work in the task of Chinese homosexual identification. Firstly, …...

. We describe a corpus analysis method for generating an ontology in the field of e- recruitment from millions of user profiles gathered on social networks and tens of thousands of job offers collected over the internet. Using statistics and n-gram analyses, we create a structured set of terms and …...

. Recurrent Neural Networks have proved effective on several NLP tasks. Despite such great success, their ability to model sequence labeling is still limited. This lead research toward solutions where RNNs are combined with models successfully employed in this context, like CRFs. In this work we propose a simpler solution: …...

. Recurrent Neural Networks have proved effective on several NLP tasks. Despite such great success, their ability to model sequence labeling is still limited. This lead research toward solutions where RNNs are combined with models successfully employed in this context, like CRFs. In this work we propose a simpler solution: …...

AbstractAlthough many sentiment lexicons in different languages exist, most are not comprehensive. In a recent sentiment analysis application, we used a large Chinese sentiment lexicon and found that it missed a large number of sentiment words in social media. This prompted us to make a new attempt to study sentiment …...

We investigate the problem of extracting mentions of medications and adverse drug events using sequence labelling and non- sequence labelling methods. We experi- ment with three different methods on two different datasets, one from a patient fo- rum with noisy text and one containing narrative patient records. An analysis of …...

The automatic detection of negation and speculation in clinical notes is vital when searching for genuine instances of a given phenomenon. This paper describes a new corpus of negation and speculation data, in the veterinary clinical note domain, and describes a series of experiments whereby we port a CRF-based method …...

The acoustic features used in forensic voice comparison (FVC) are correlated in almost all cases. A sizeable proportion of FVC studies and casework has relied, for statistical modelling, on the multivariate kernel density likelihood ratio (MVKDLR) formula, which considers the correlations between the features and computes an overall combined likelihood …...

Transcription of speech is an important part of language documentation, and yet speech recognition technology has not been widely harnessed to aid linguists. We explore the use of a neural network ar- chitecture with the connectionist tempo- ral classification loss function for phone- mic and tonal transcription in a language …...

Ensemble techniques are powerful ap- proaches that combine several weak learn- ers to build a stronger one. As a meta learning framework, ensemble techniques can easily be applied to many machine learning techniques. In this paper we propose a neural network extended with an ensemble loss function for text clas- …...

The task of document quality assessment is a highly complex one, which draws on analysis of aspects including linguistic content, document structure, fact correct- ness, and community norms. We explore the task in the context of a Wikipedia ar- ticle assessment task, and propose a hy- brid approach combining deep …...

This paper presents a deep linguistic atten- tional framework which incorporates word level concept information into neural clas- sification models. While learning neural classification models often requires a large amount of labelled data, linguistic concept information can be obtained from exter- nal knowledge, such as pre-trained word embeddings, WordNet for …...

Answering questions while reasoning over multiple supporting facts has long been a goal of artificial intelligence. Re- cently, remarkable advances have been made, focusing on reasoning over natu- ral language-based stories. In particu- lar, end-to-end memory networks (N2N), have achieved state-of-the-art results over such tasks. However, N2Ns are limited by …...

In the last few years, machine learning has become a very popular tool for an- alyzing financial text data, with many promising results in stock price fore- casting from financial news, a devel- opment with implications for the Effi- cient Markets Hypothesis (EMH) that underpins much economic theory. In this …...