## 1 Introduction  
The advancing technology has evolved into an integral part of our daily lives, and the need for software products is rising constantly. Indeed, software is a technological outcome in itself and is the tool that enables individuals to use technology. As utilized in almost every field, it is possible to define these tools as requirement-oriented software products. The development of a software application consists of successive stages, such as planning, requirements analysis, design, coding, testing, and maintenance, in a specific lifecycle. Software requirements analysis is one of the most fundamental and critical stages of the software development lifecycle since the development process of software applications often relies on satisfying specific customer needs [1]. Hence, it is crucial to explicitly identify the demand's nature, the requirements it addresses, and the services it will provide. Accordingly, software requirements analysis potentially refers to the stages in identifying, outlining, categorizing, and prioritizing steps of the software requirements. In the software requirement analysis phase, requirement engineers or project analysts attempt to ascertain the demanded system needs in collaboration with the demandant. Accordingly, they generate the software requirement document in light of the identified requirements and share it with all stakeholders. Afterward, requirements engineers or business analysts examine the needs specified in the requirements document in detail. Consequently, they categorize them as functional requirements (FR) and non-functional requirements (NFR) based on the intended use of the system. FR is defined as the actionsthat a product should satisfy by specifying the corresponding features and functions. Furthermore, FR is the specifications of the software details listed directly by the stakeholders, the services provided by the system, and the necessary limits of the system. NFR, also referred to as the quality characteristics of the software, may be expressed as the general features of the system such as response time, performance, security, and usability. Correct classification of FR and NFR will directly impact the project's success since the software requirements classification will serve as a guideline for other stages, such as designing and coding, in the software life cycle [2]. However, as FR and NFR are natural language texts within the same requirement document, they are likely to be confused and pose a challenging task to identify manually. The lack of FR in the developed software system leads to system failure, correspondingly, ignoring NFR results in project failure, loss of system integrity, or cost increase [3; 4]. This study used machine learning (ML) approaches on a Turkish dataset generated specifically for software requirements analysis, aiming to develop ML algorithms for the automatic classification of software requirements. Since the documentation of the requirements was written in natural language in the text format, natural language processing methods have been applied in addition to ML algorithms. This study also executed experimental designs using conventional machine learning algorithms, deep learning algorithms, and transformer models. Correspondingly, the results acquired from the experimental studies were subject to comparisons through performance evaluation criteria. The contribution of this study to the current literature may be summarized as follows: (i) developing a software requirement analysis dataset in the Turkish language for the first time using real software projects from various platforms and industries, (ii) utilizing intricate language processing protocols in Turkish, which is a morphologically rich language, (iii) obtaining the most optimally model by utilizing all algorithm types in the ML literature, and (iv) being the most detailed experimental study in this field in the Turkish language. Following an introduction text in Section 1, Section 2 involves subject-related topics.