20 citations · 20 across the 4 of their papers we have counts for
9 papers
Personal Attribute Leakage in Federated Speech Models
Hamdan Al-Ali, Ali Reza Ghavamipour, Tommaso Caselli +3
Federated learning is a common method for privacy-preserving training of machine learning models. In this paper, we analyze the vulnerability of ASR models to attribute inference a…
RelUNet: Relative Channel Fusion U-Net for Multichannel Speech Enhancement
Ibrahim Aldarmaki, Thamar Solorio, Bhiksha Raj +1
Neural multi-channel speech enhancement models, in particular those based on the U-Net architecture, demonstrate promising performance and generalization potential. These models ty…
PALM: Few-Shot Prompt Learning for Audio Language Models
Asif Hanif, Maha Tufail Agro, Mohammad Areeb Qazi +1
Audio-Language Models (ALMs) have recently achieved remarkable success in zero-shot audio recognition tasks, which match features of audio waveforms with class-specific text prompt…
Mixat: A Data Set of Bilingual Emirati-English Speech
Maryam Al Ali, Hanan Aldarmaki
This paper introduces Mixat: a dataset of Emirati speech code-mixed with English. Mixat was developed to address the shortcomings of current speech recognition resources when appli…
Homograph Disambiguation Through Selective Diacritic Restoration
Sawsan Alqahtani, Hanan Aldarmaki, Mona Diab
Lexical ambiguity, a challenging phenomenon in all natural languages, is particularly prevalent for languages with diacritics that tend to be omitted in writing, such as Arabic. Om…
Efficient Sentence Embedding using Discrete Cosine Transform
Nada Almarwani, Hanan Aldarmaki, Mona Diab
Vector averaging remains one of the most popular sentence embedding methods in spite of its obvious disregard for syntactic structure. While more complex sequential or convolutiona…