This paper introduces the Corpus of Arabic Competitive Debates (Munazarat). Despite the significance of competitive debating as an activity of fostering critical thinking and promoting dialogue, researchers within the fields of Arabic Natural Language Processing (NLP), linguistics, argumentation studies, and education have access to very limited datasets about competitive debating. At this study stage, we introduce Munazarat 1.0, which combines recordings of approximately 50 hours collected from 73 debates at QatarDebate-recognized tournaments, where all of those debates were available on YouTube. Munazarat is a novel specialized speech Arabic corpus, mostly in Modern Standard Arabic (MSA), consisting of diverse debating topics and showing rich metadata for each debate. The transcription of debates was done using Fenek, a speech-to-text Kanari AI tool, and three native Arabic speakers reviewed each transcription file to enhance the quality provided by the machine. The Munazarat 1.0 dataset can be used to train Arabic NLP tools, develop an argumentation mining machine, and analyze Arabic argumentation and rhetoric styles. Keywords: Arabic Speech Corpus, Modern Standard Arabic, Debates