(AI-generated image)
Imagine you’ve just wrapped up an audio translation project, recording the book of Luke into a North African language. And you are feeling relieved after months of hard work. But during the review phase, a few glaring issues emerge: background noise (a rooster crowing, footsteps, the occasional honking of car horns) which compromises the quality of the recording. One of the voice actors, who had previously agreed to participate, now expresses discomfort with their voice being used, citing personal reasons. On top of that, a key term in the translation was mispronounced throughout the entire recording, requiring a correction in multiple places. The thought of re-recording everything feels overwhelming.
It’s not uncommon for an Oral Bible Translation (OBT) project to encounter one or more of these challenges, and the hypothetical scenario described above encapsulates some of the most common real-world issues that OBT teams have shared with us, the AI Capabilities Team. Through our partnership with OBT teams, we’ve begun exploring ways to leverage advances in artificial intelligence to help address these time- and resource-consuming problems, which has resulted in a new suite of tools called AERO (AI-Enhancements Responsive to Orality). AERO currently provides Noise Removal, Voice Conversion, and Transcription via a user interface and API. There are additional features, including audio infilling, which are actively under development.
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