AI and machine learning are being used more frequently in transcription and translation. These Hybrid Transcription and Translation services can offer a host of benefits since they involve a more integrated collaboration between both machine and human translators, thus ensuring the best possible outcome.
Data Integration and Training The Machine Translation
AI transcription and translation allow large volumes of work to be carried out in a short space of time. While a human transcriptionist or translator would take many hours, days, or even longer to produce the transcription of an extremely long video or audio recording, or the translation of a full-length book, AI and machine learning can deliver results in a far shorter timeframe. However, training machine translation and AI means that bilingual data that includes both the source and target languages must be prepared and processed, and a vocabulary list must be built. Furthermore, human translators are frequently required to check that those prepared lists are suitably diverse and unbiased, as well as to ensure that the translated data is consistent and error-free.
Human Involvement For Inaudible Audio
When transcribing and translating audio recordings, AI may sometimes fail to detect sections of the recording that are difficult to hear or make out. In those cases, human ears may be able to detect and clarify those inaudible sections. Thus, humans and machines can work together to produce a complete and comprehensive transcription of the full recording and to train the AI system so that it can learn how to decipher similar inaudible sections in future in order to reduce the need for human intervention.
Overcoming Language Nuances And Idioms
All languages contain their own unique expressions, idioms, and cultural references that are extremely challenging for any machine translation model to capture accurately. This is another situation in which human translators can prove to be indispensable. As translators with native fluency in the target language, they can balance the literal translation of the text with a more contextual understanding in order to produce a version that communicates with the target audience in the most effective manner.
The Solution Is Evaluation And Quality Assurance
While AI and machine translation is now a key component of many large-scale transcription and translation projects, it cannot fully replace the need for human input. AI is invaluable for translating documents, recordings, and more in high volumes, but as yet, it cannot always create a correctly contextualised translation that communicates in the most effective way with the reader or audience. Therefore, the involvement of expert human translators is essential to minimise the volume of post-editing, and to assess the fluency and accuracy of the translation produced by the machine system. Only a human translator can ensure that the final result contains the necessary language nuances and context to engage with the target audience, thus overcoming the challenges that are faced within the realm of AI and machine transcription and translation through a hybrid model that blends the best of both worlds.
