A complete KALDI recipe for building Arabic speech recognition systems

In this paper we present a recipe and language resources for training and testing Arabic speech recognition systems using the KALDI toolkit. We built a prototype broadcast news system using 200 hours GALE data that is publicly available through LDC. We describe in detail the decisions made in building the system: using the MADA toolkit for text normalization and vowelization; why we use 36 phonemes; how we generate pronunciations; how we build the language model. We report results using state-of-the-art modeling and decoding techniques. The scripts are released through KALDI and resources are made available on QCRI´s language resources web portal. This is the first effort to share reproducible sizable training and testing results on MSA system.