<![CDATA[This study uses a descriptive qualitative approach to examine the translation techniques used in the translated version of the song "Shake It Off" by Taylor Swift into Indonesian. The analysis compares two translations, namely the subtitle from YouTube (TT1) and the machine translation using the platform DeepL (TT2). This study refers to the framework of translation techniques developed by Molina and Albir (2002), as well as the interactive data analysis model of Miles and Huberman (1994) which includes the process of data condensation, data presentation, and conclusion drawing. The song lyrics were divided into units of analysis and arranged parallel to their respective translated versions to identify and classify the techniques used. The findings show that there is a significant difference in the application of translation strategies between TT1 and TT2. TT2 relies heavily on literal translation techniques (68 cases or 39.5%), reflecting the tendency to maintain the surface structure of the source text. In contrast, TT1 shows a higher diversity of techniques, especially adaptation (28 cases or 16.2%) and reduction (11 cases or 6.3%) techniques, reflecting the translator's sensitivity to the cultural context and audiovisual limitations. Other techniques such as amplification, borrowing and modulation also show variations in frequency of use between the two versions. In general, this study shows that human and machine interpreters have different priorities in conveying meaning, style and nuance in the context of translating song lyrics. These differences provide important insights into the advantages and limitations of each approach in the field of audiovisual translation.]]>
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