2 citations · 8 across the 18 of their papers we have counts for
19 papers
CS-YODAS: A Mined Dataset of In-the-Wild Code-Switched Speech
Brian Yan, Qingzheng Wang, Matthew Wiesner +9
We present CS-YODAS, a Creative Commons-licensed dataset of in-the-wild code-switched speech mined from multilingual YouTube data. Code-switching (CS), or the alternation between l…
CS-FLEURS: A Massively Multilingual and Code-Switched Speech Dataset
Brian Yan, Injy Hamed, Shuichiro Shimizu +24
We present CS-FLEURS, a new dataset for developing and evaluating code-switched speech recognition and translation systems beyond high-resourced languages. CS-FLEURS consists of 4…
BALSAM: A Platform for Benchmarking Arabic Large Language Models
Rawan Al-Matham, Kareem Darwish, Raghad Al-Rasheed +40
The impressive advancement of Large Language Models (LLMs) in English has not been matched across all languages. In particular, LLM performance in Arabic lags behind, due to data s…
Tell me Habibi, is it Real or Fake?
Kartik Kuckreja, Parul Gupta, Injy Hamed +3
Deepfake generation methods are evolving fast, making fake media harder to detect and raising serious societal concerns. Most deepfake detection and dataset creation research focus…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
The Impact of Code-switched Synthetic Data Quality is Task Dependent: Insights from MT and ASR
Injy Hamed, Ngoc Thang Vu, Nizar Habash
Code-switching, the act of alternating between languages, emerged as a prevalent global phenomenon that needs to be addressed for building user-friendly language technologies. A ma…
A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions
Injy Hamed, Caroline Sabty, Slim Abdennadher +3
Language in the Arab world presents a complex diglossic and multilingual setting, involving the use of Modern Standard Arabic, various dialects and sub-dialects, as well as multipl…
NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Amr Keleg, AbdelRahim Elmadany +5
We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024). NADI's objective is to help advance SoTA Arabic NLP by providing guidance, data…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…
ZAEBUC-Spoken: A Multilingual Multidialectal Arabic-English Speech Corpus
Injy Hamed, Fadhl Eryani, David Palfreyman +1
We present ZAEBUC-Spoken, a multilingual multidialectal Arabic-English speech corpus. The corpus comprises twelve hours of Zoom meetings involving multiple speakers role-playing a…
Data Augmentation Techniques for Machine Translation of Code-Switched Texts: A Comparative Study
Injy Hamed, Nizar Habash, Ngoc Thang Vu
Code-switching (CSW) text generation has been receiving increasing attention as a solution to address data scarcity. In light of this growing interest, we need more comprehensive s…
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…
ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic - English
Injy Hamed, Nizar Habash, Slim Abdennadher +1
We present our work on collecting ArzEn-ST, a code-switched Egyptian Arabic - English Speech Translation Corpus. This corpus is an extension of the ArzEn speech corpus, which was c…
Exploring Segmentation Approaches for Neural Machine Translation of Code-Switched Egyptian Arabic-English Text
Marwa Gaser, Manuel Mager, Injy Hamed +3
Data sparsity is one of the main challenges posed by code-switching (CS), which is further exacerbated in the case of morphologically rich languages. For the task of machine transl…
The Who in Code-Switching: A Case Study for Predicting Egyptian Arabic-English Code-Switching Levels based on Character Profiles
Injy Hamed, Alia El Bolock, Cornelia Herbert +2
Code-switching (CS) is a common linguistic phenomenon exhibited by multilingual individuals, where they tend to alternate between languages within one single conversation. CS is a…
Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentation
Injy Hamed, Nizar Habash, Slim Abdennadher +1
Data sparsity is a main problem hindering the development of code-switching (CS) NLP systems. In this paper, we investigate data augmentation techniques for synthesizing dialectal…
Predicting User Code-Switching Level from Sociological and Psychological Profiles
Injy Hamed, Alia El Bolock, Nader Rizk +3
Multilingual speakers tend to alternate between languages within a conversation, a phenomenon referred to as "code-switching" (CS). CS is a complex phenomenon that not only encompa…
Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech
Injy Hamed, Pavel Denisov, Chia-Yu Li +3
Code-switching (CS), defined as the mixing of languages in conversations, has become a worldwide phenomenon. The prevalence of CS has been recently met with a growing demand and in…
Code-switching Language Modeling With Bilingual Word Embeddings: A Case Study for Egyptian Arabic-English
Injy Hamed, Moritz Zhu, Mohamed Elmahdy +2
Code-switching (CS) is a widespread phenomenon among bilingual and multilingual societies. The lack of CS resources hinders the performance of many NLP tasks. In this work, we expl…