title: Optimized WFST-Based ASR for Arabic: Balancing Memory, Speed, and Accuracy
abstract: Weighted Finite-State Transducers (WFSTs) have revolutionized Automatic Speech Recognition (ASR) by enabling significantly faster decoding speeds compared to traditional systems that build the search space progressively. However, applying WFSTs to morphology-rich languages such as Arabic presents challenges due to the large vocabulary, resulting in extensive networks that exceed the memory capacity of standard CPUs. This study introduces various strategies to reduce the size of large vocabulary 
journal: Journal of Computer Science