<![CDATA[In the digital era, automatic transcription is a crucial solution for converting audio content into text, especially in the context of academic documentation. The main challenge in this process is transcription accuracy, which can be affected by the quality of the audio file, including its bitrate and file size. This study aims to analyze the impact of MP3 bitrate and file size on transcription accuracy using the Whisper large-v3 model. Five academic audio files were converted into five different bitrate levels, ranging from 64 kbps to 320 kbps, and then transcribed automatically using the Whisper model. Evaluation was conducted by calculating the Word Error Rate (WER) as an indicator of transcription accuracy. In addition, processing time and file size were recorded to analyze transcription efficiency. The results show that increasing bitrate does not always lead to higher accuracy. Bitrates of 128–192 kbps provided the best balance between transcription accuracy, processing efficiency, and file size. This study makes a significant contribution to the development of automatic transcription systems based on ASR models, particularly for audio documentation needs in educational institutions. These findings serve as a technical reference for developing efficient and accurate audio documentation systems in academic environments.]]>
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