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20152023
most citedLAraBench: Benchmarking Arabic AI with Large Language Models

14 citations · 39 across the 15 of their papers we have counts for

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5 papers · 1 filter

eess.AS2023★ 1 cited

FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator

Massa Baali, Ahmed Ali

This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise. The application gets the text from the user, applie…

eess.AS2023

QVoice: Arabic Speech Pronunciation Learning Application

Yassine El Kheir, Fouad Khnaisser, Shammur Absar Chowdhury +3

This paper introduces a novel Arabic pronunciation learning application QVoice, powered with end-to-end mispronunciation detection and feedback generator module. The application is…

eess.AS2022

Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition

Injy Hamed, Amir Hussein, Oumnia Chellah +5

Code-switching poses a number of challenges and opportunities for multilingual automatic speech recognition. In this paper, we focus on the question of robust and fair evaluation m…

eess.AS2021

Arabic Speech Recognition by End-to-End, Modular Systems and Human

Amir Hussein, Shinji Watanabe, Ahmed Ali

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 hum…

eess.AS2020

Word Error Rate Estimation Without ASR Output: e-WER2

Ahmed Ali, Steve Renals

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-consum…