5 accepted papers
Despite progress in Arabic large language models, such as Jais and AceGPT, their evaluation on commonsense reasoning has largely relied on machine-translated datasets, which lack cultural depth and may introduce Anglocentric biases. Commonsense reasoning is shaped by geographical and cultural contex…
Recent work on distilling Whisper’s knowledge into small models using pseudo-labels shows promising performance while reducing the size by up to 50%. This results in small, efficient, and dedicated models. However, a critical step of distillation using pseudo-labels involves filtering high-quality p…
In spite of the recent progress in speech processing, the majority of world languages and dialects remain uncovered. This situation only furthers an already wide technological divide, thereby hindering technological and socioeconomic inclusion. This challenge is largely due to the absence of dataset…
Code-switching in speech, particularly between languages that use different scripts, can potentially be correctly transcribed in various forms, including different ways of transliteration of the embedded language into the matrix language script. Traditional methods for measuring accuracy, such as Wo…
Arabic is known to present unique challengesfor Automatic Speech Recognition (ASR). Onone hand, its rich linguistic diversity andwide range of dialects complicate the de-velopment of robust, inclusive models. Onthe other, current multilingual ASR modelsare compute-intensive and lack proper com-prehe…