A Comparative Analysis of Machine Translation and Human Translation: Efficacy of Poetry Translation from Urdu to English
DOI:
https://doi.org/10.63283/IRJ.04.01/02Keywords:
Neural Machine Translation, Google Translate, Berman’s Model, Iqbal’s Poetry, Deforming TendenciesAbstract
Poetry is essentially the most condensed and pragmatically loaded form of art. The daunting task of effectively translating poetry requires avant-garde translating acumen. With the advent of neural machine translation, the debate on Human vs. Machine Translation and the speculation of Machine Translation replacing humans went rife. The current study aims to gauge the efficacy of Google Translate’s (MT) rendering of Iqbal’s poem La Illaha Ilallah as compared to Bashir Ahmed Dar’s Human Translation (HT) of the same poem. Bahir Ahmed Dar published his English translation of the chosen poem in his book ‘Rod of Moses’. This study examines the impact of Antoine Berman’s deforming tendencies on the Machine and Human English translations of Iqbal’s poem La Illaha Ilallah. Moreover, the study aims to find out how lexical elements change in the translations of the source language to make it suitable for the target language audience by adopting the deforming tendencies. It is a qualitative type of study employing Berman’s Model of Twelve Deforming Tendencies to analyze which strategies were used in both the English translation of Iqbal’s Urdu poem. The data of the Source Urdu Text was collected from the Internet Archive, and that of Human Translation was taken from Bashir A. Dar’s book Rod of Moses. To generate the Machine Translation, Google Translate was used to generate the MT output. The results indicated that the MT of the work suffered from lexical mismatches, destruction of rhythm and destruction of vernacular networks, rendering an erroneous and vague translation, while HT managed to retain the cultural and contextual essence of the source text. The findings also revealed that the Human translation also faced many deformative tendencies but successfully maintained the genre and social stance of the author. Overall, it appears that poetry translation may benefit from a human translator's profound attention to cultural and contextual detail, which is ignored by NMT tools such as Google Translate, leading to inconsistencies in the translation.
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