Abstract
In recent years, the research pertaining to speech recognition technology in the Kazakh language has gained significant importance. This is due to the increasing demand for natural language processing applications in the region where Kazakh is predominantly spoken. Thus, there exists an urgent requirement for precise and dependable speech recognition systems. The research study examines the application of sophisticated deep learning methodologies, such as Natural Language Processing (NLP) and Hidden Markov Model (HMM), in facilitating speech recognition for the Kazakh language. Additionally, the investigation delves into how various techniques, including data preprocessing, acoustic modeling, and language modeling, can aid in devising effective speech recognition systems. The article deliberates on the feasible uses of speech recognition technology in the geographic area where Kazakh language is spoken and outlines its future research prospects. The investigation underscores the significance of persistent inquiry in this realm to confront distinctive obstacles encountered in creating speech recognition systems for languages with restricted resources.