Search Results for author:
Found 21 papers, 5 papers with code
Improving Arabic Text Categorization Using Transformer Training Diversification
Automatic categorization of short texts, such as news headlines and social media posts, has many applications ranging from content analysis to recommendation systems.
SpeechBlender: Speech Augmentation Framework for Mispronunciation Data Generation
With SpeechBlender augmentation, we observed a 3% and 2% increase in Pearson correlation coefficient (PCC) compared to no-augmentation and goodness of pronunciation augmentation scenarios respectively for Speechocean762 testset.
What can Speech and Language Tell us About the Working Alliance in Psychotherapy
To the best of our knowledge, this is the first and a novel study to exploit speech and language for characterising working alliance.
ArabGend: Gender Analysis and Inference on Arabic Twitter
Gender analysis of Twitter can reveal important socio-cultural differences between male and female users.
Emojis as Anchors to Detect Arabic Offensive Language and Hate Speech
We evaluate our models on external datasets - a Twitter dataset collected using a completely different method, and a multi-platform dataset containing comments from Twitter, YouTube and Facebook, for assessing generalization capability.
ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination
We studied the data for individual types of tweets and temporal changes in stance towards vaccine.
Textual Data Augmentation for Arabic-English Code-Switching Speech Recognition
The pervasiveness of intra-utterance code-switching (CS) in spoken content requires that speech recognition (ASR) systems handle mixed language.
QASR: QCRI Aljazeera Speech Resource A Large Scale Annotated Arabic Speech Corpus
We also report the first baseline for Arabic punctuation restoration.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+8
A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models
In this study, we first provide a review of Bangla NLP tasks, resources, and tools available to the research community; we benchmark datasets collected from various platforms for nine NLP tasks using current state-of-the-art algorithms (i. e., transformer-based models).
What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis
Our results reveal: (i) channel and gender information is omnipresent and is redundantly distributed (ii) complex properties such as dialectal information is encoded only in the task-oriented pretrained network and is localised in the upper layers (iii) a minimal subset of neurons can be extracted to encode the predefined property (iv) salient neurons are sometimes shared between properties and can highlights presence of biases in the network.
QASR: QCRI Aljazeera Speech Resource -- A Large Scale Annotated Arabic Speech Corpus
We also report the first baseline for Arabic punctuation restoration.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+8
Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASR
We evaluate the system performance handling: (i) monolingual (Ar, En and Fr); (ii) multi-dialectal (Modern Standard Arabic, along with dialectal variation such as Egyptian and Moroccan); (iii) code-switching -- cross-lingual (Ar-En/Fr) and dialectal (MSA-Egyptian dialect) test cases, and compare with current state-of-the-art systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Sentiment Classification in Bangla Textual Content: A Comparative Study
In this study, we explore several publicly available sentiment labeled datasets and designed classifiers using both classical and deep learning algorithms.
A Multi-Platform Arabic News Comment Dataset for Offensive Language Detection
Hence, it is important to detect offensive comments in social media platforms.
ALT Submission for OSACT Shared Task on Offensive Language Detection
In this paper, we describe our efforts at OSACT Shared Task on Offensive Language Detection.
An LSTM Adaptation Study of (Un)grammaticality
We propose a novel approach to the study of how artificial neural network perceive the distinction between grammatical and ungrammatical sentences, a crucial task in the growing field of synthetic linguistics.
RNN Simulations of Grammaticality Judgments on Long-distance Dependencies
The paper explores the ability of LSTM networks trained on a language modeling task to detect linguistic structures which are ungrammatical due to extraction violations (extra arguments and subject-relative clause island violations), and considers its implications for the debate on language innatism.
Depression Severity Estimation from Multiple Modalities
In this AVEC challenge we explore different modalities (speech, language and visual features extracted from face) to design and develop automatic methods for the detection of depression.
Functions of Silences towards Information Flow in Spoken Conversation
It is also observed that sometimes long silences can be used deliberately to get a forced response from another speaker thus making silence a multi-functional and an important catalyst towards information flow.
How Interlocutors Coordinate with each other within Emotional Segments?
In this paper, we aim to investigate the coordination of interlocutors behavior in different emotional segments.
Transfer of Corpus-Specific Dialogue Act Annotation to ISO Standard: Is it worth it?
In this paper we test the utility of the ISO standard through comparative evaluation of the corpus-specific legacy and the semi-automatically transferred DiAML DA annotations on supervised dialogue act classification task.
