Abstract Speech acts are a fundamental aspect of communication, enabling speakers to perform actions through language. Despite extensive research in pragmatics, a gap remains in understanding how speech acts manifest in spontaneous, everyday conversations across diverse social contexts. This study addresses this gap by exploring the use, interpretation, and variations of speech acts in informal interactions, focusing on how speakers navigate politeness, intention, and context. Grounded in Searle’s Speech Act Theory and supplemented by Brown and Levinson’s Politeness Theory, the research adopts a qualitative methodology to provide a detailed pragmatic analysis of conversational data. Using purposive sampling, 20 participants from diverse cultural and linguistic backgrounds were recorded in naturalistic settings, capturing everyday conversations. Data were analyzed using discourse analysis to identify patterns, functions, and contextual variations in the use of speech acts. The findings reveal significant variations in speech act realization influenced by cultural norms, interpersonal relationships, and conversational goals. Key speech acts such as requests, apologies, and directives often align with or deviate from theoretical models, highlighting the dynamic nature of real-world language use. This study contributes to the field by demonstrating the need to refine existing theories to account for contextual fluidity and individual speaker strategies. The implications of this research extend to language education, where a deeper understanding of pragmatic competence can enhance second language learners’ ability to navigate authentic conversational contexts. By bridging theoretical frameworks with real-world application, this study advances both academic understanding and practical tools for improving communication skills in multilingual and multicultural environments. Keywords: Speech Acts, Pragmatics, Context-Dependent Communication, Interpersonal Relationships, Searle’s Speech Act Theory.
                        
                        
                        
                        
                            
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