Search Results for author:
Found 52 papers, 14 papers with code
A Control Theoretic Study on Omnidirectional MAVs with Minimum Number of Actuators and No Internal Forces at Any Orientation
We propose a new multirotor aerial vehicle class of designs composed of a multi-body structure in which a main body is connected by passive joints to links equipped with propellers.
Beyond Orthography: Automatic Recovery of Short Vowels and Dialectal Sounds in Arabic
Phonetically correct transcribed speech resources for dialectal Arabic are scarce.
Automatic Pronunciation Assessment -- A Review
Pronunciation assessment and its application in computer-aided pronunciation training (CAPT) have seen impressive progress in recent years.
Speech collage: code-switched audio generation by collaging monolingual corpora
Designing effective automatic speech recognition (ASR) systems for Code-Switching (CS) often depends on the availability of the transcribed CS resources.
L1-aware Multilingual Mispronunciation Detection Framework
The phonological discrepancies between a speaker's native (L1) and the non-native language (L2) serves as a major factor for mispronunciation.
The complementary roles of non-verbal cues for Robust Pronunciation Assessment
Research on pronunciation assessment systems focuses on utilizing phonetic and phonological aspects of non-native (L2) speech, often neglecting the rich layer of information hidden within the non-verbal cues.
LLMeBench: A Flexible Framework for Accelerating LLMs Benchmarking
In this study, we introduce the LLMeBench framework, which can be seamlessly customized to evaluate LLMs for any NLP task, regardless of language.
MyVoice: Arabic Speech Resource Collaboration Platform
Furthermore, the platform offers flexibility to admin roles to add new data or tasks beyond dialectal speech and word collection, which are displayed to contributors.
FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator
This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise.
LAraBench: Benchmarking Arabic AI with Large Language Models
Our findings provide valuable insights into the applicability of LLMs for Arabic NLP and speech processing tasks.
QVoice: Arabic Speech Pronunciation Learning Application
This paper introduces a novel Arabic pronunciation learning application QVoice, powered with end-to-end mispronunciation detection and feedback generator module.
Multilingual Word Error Rate Estimation: e-WER3
The success of the multilingual automatic speech recognition systems empowered many voice-driven applications.
Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Study
Several high-resource Text to Speech (TTS) systems currently produce natural, well-established human-like speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition
Code-switching poses a number of challenges and opportunities for multilingual automatic speech recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
SpeechBlender: Speech Augmentation Framework for Mispronunciation Data Generation
Our proposed technique achieves state-of-the-art results, with Speechocean762, on ASR dependent mispronunciation detection models at phoneme level, with a 2. 0% gain in Pearson Correlation Coefficient (PCC) compared to the previous state-of-the-art [1].
Ranked #4 on
Phone-level pronunciation scoring
on speechocean762
Ten Years after ImageNet: A 360° Perspective on AI
The rise of attention networks, self-supervised learning, generative modeling, and graph neural networks has widened the application space of AI.
Creating Speech-to-Speech Corpus from Dubbed Series
We propose an unsupervised approach to construct speech-to-speech corpus, aligned on short segment levels, to produce a parallel speech corpus in the source- and target- languages.
ClassSPLOM -- A Scatterplot Matrix to Visualize Separation of Multiclass Multidimensional Data
In multiclass classification of multidimensional data, the user wants to build a model of the classes to predict the label of unseen data.
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
Arabic Code-Switching Speech Recognition using Monolingual Data
Code-switching in automatic speech recognition (ASR) is an important challenge due to globalization.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis
In our study, we conduct a post-hoc functional interpretability analysis of pretrained speech models using the probing framework [1].
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
Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognition
In this paper, we exploit the transfer learning approach to design End-to-End (E2E) CS ASR systems for the two low-resourced language pairs using different monolingual speech data and a small set of noisy CS data.
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
Arabic Speech Recognition by End-to-End, Modular Systems and Human
Recent advances in automatic speech recognition (ASR) have achieved accuracy levels comparable to human transcribers, which led researchers to debate if the machine has reached human performance.
Tetraquark Interpretation and Production Mechanism of the Belle $Y_b (10750)$-Resonance
Recently, the Belle Collaboration has updated the analysis of the cross sections for the processes $e^+ e^- \to \Upsilon(nS)\, \pi^+ \pi^-$ ($n = 1,\, 2,\, 3$) in the $e^+ e^-$ center-of-mass energy range from 10. 52 to 11. 02~GeV.
High Energy Physics - Phenomenology High Energy Physics - Experiment
Interpretation of LHCb Hidden-Charm Pentaquarks within the Compact Diquark Model
We interpret these narrow resonances as compact hidden-charm diquark-diquark-antiquark pentaquarks.
High Energy Physics - Phenomenology High Energy Physics - Experiment
Efficient Arabic emotion recognition using deep neural networks
The second architecture is based on a deep CNN model.
Word Error Rate Estimation Without ASR Output: e-WER2
Measuring the performance of automatic speech recognition (ASR) systems requires manually transcribed data in order to compute the word error rate (WER), which is often time-consuming and expensive.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context
Alternatively, we can profile entire news outlets and look for those that are likely to publish fake or biased content.
Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Information
Our analysis shows that the use of acoustic signal helped to improve bias detection by more than 6% absolute over using text and metadata only.
Detecting Deception in Political Debates Using Acoustic and Textual Features
We present work on deception detection, where, given a spoken claim, we aim to predict its factuality.
DARTS: Dialectal Arabic Transcription System
We analyze the following; transfer learning from high resource broadcast domain to low-resource dialectal domain and semi-supervised learning where we use in-domain unlabeled audio data collected from YouTube.
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition
End-to-end neural network systems for automatic speech recognition (ASR) are trained from acoustic features to text transcriptions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Domain Attentive Fusion for End-to-end Dialect Identification with Unknown Target Domain
An important issue for end-to-end systems is to have some knowledge of the application domain, because the system can be vulnerable to use cases that were not seen in the training phase; such a scenario is often referred to as a domain mismatched condition.
Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign
We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects.
Word Error Rate Estimation for Speech Recognition: e-WER
Measuring the performance of automatic speech recognition (ASR) systems requires manually transcribed data in order to compute the word error rate (WER), which is often time-consuming and expensive.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Convolutional Neural Networks and Language Embeddings for End-to-End Dialect Recognition
Although the Siamese network with language embeddings did not achieve as good a result as the end-to-end DID system, the two approaches had good synergy when combined together in a fused system.
Sound Audio and Speech Processing
WERd: Using Social Text Spelling Variants for Evaluating Dialectal Speech Recognition
We study the problem of evaluating automatic speech recognition (ASR) systems that target dialectal speech input.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Speech Recognition Challenge in the Wild: Arabic MGB-3
Two hours of audio per dialect were released for development and a further two hours were used for evaluation.
MIT-QCRI Arabic Dialect Identification System for the 2017 Multi-Genre Broadcast Challenge
In order to achieve a robust ADI system, we explored both Siamese neural network models to learn similarity and dissimilarities among Arabic dialects, as well as i-vector post-processing to adapt domain mismatches.
Findings of the VarDial Evaluation Campaign 2017
We present the results of the VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects, which we organized as part of the fourth edition of the VarDial workshop at EACL{'}2017.
QCRI Live Speech Translation System
This paper presents QCRI{'}s Arabic-to-English live speech translation system.
The SUMMA Platform Prototype
We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task
We present the results of the third edition of the Discriminating between Similar Languages (DSL) shared task, which was organized as part of the VarDial{'}2016 workshop at COLING{'}2016.
The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition
For language modelling, we made available over 110M words crawled from Aljazeera Arabic website Aljazeera. net for a 10 year duration 2000-2011.
Multi-view Dimensionality Reduction for Dialect Identification of Arabic Broadcast Speech
In this work, we present a new Vector Space Model (VSM) of speech utterances for the task of spoken dialect identification.
Automatic Dialect Detection in Arabic Broadcast Speech
We used these features in a binary classifier to discriminate between Modern Standard Arabic (MSA) and Dialectal Arabic, with an accuracy of 100%.
