This study aims to evaluate the linguistic accuracy and efficiency of artificial intelligence systems in speech recognition, especially given its increasing use and integration into daily life. The focus is on identifying common transcription errors in German when using AI tools, with special attention to the grapheme-phoneme relationship, phonological deviations, morphological structures, and challenges in word segmentation.
Adopting an analytical and comparative approach, the study examines and contrasts machine-generated transcriptions with human-produced reference transcriptions. It classifies recurring error patterns within linguistic frameworks, based on the analysis of 200 audio files for which human transcriptions are available.
The findings highlight several key results, most notably that AI-generated transcriptions exhibit significant weaknesses, specifically in handling the complicated relationship between graphemes and phonemes. In addition to the language-specific phenomena in German, such as homophones, inflectional forms and present major challenges that AI systems often struggle to process accurately.
Abuelela, H. A. S. (2025). Problems of the Grapheme-Phoneme Relationship in German in AI-based Speech Recognition Systems. فيلولوجى: سلسلة الدراسات الأدبية واللغوية, 42(83), 43-64. doi: 10.21608/gsal.2025.433052
MLA
Hanaa Ahmed Sayed Abuelela. "Problems of the Grapheme-Phoneme Relationship in German in AI-based Speech Recognition Systems", فيلولوجى: سلسلة الدراسات الأدبية واللغوية, 42, 83, 2025, 43-64. doi: 10.21608/gsal.2025.433052
HARVARD
Abuelela, H. A. S. (2025). 'Problems of the Grapheme-Phoneme Relationship in German in AI-based Speech Recognition Systems', فيلولوجى: سلسلة الدراسات الأدبية واللغوية, 42(83), pp. 43-64. doi: 10.21608/gsal.2025.433052
VANCOUVER
Abuelela, H. A. S. Problems of the Grapheme-Phoneme Relationship in German in AI-based Speech Recognition Systems. فيلولوجى: سلسلة الدراسات الأدبية واللغوية, 2025; 42(83): 43-64. doi: 10.21608/gsal.2025.433052
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