In May 2024, researchers emphasized the crucial role that emotions play in human communication and introduced a new dataset designed to enhance speech-to-text and speech-to-speech translation by integrating emotional context into the translation process.

In July 2024, Alibaba incorporated speech emotion recognition (SER) into its FunAudioLLM to retain original emotions in AI-powered interpreting.

Building on this, an August 6, 2024, paper by Charles Brazier and Jean-Luc Rouas from the University of Bordeaux demonstrated how to integrate emotional context into large language models (LLMs) to condition translation and improve quality.

They argue that “conditioning the translation with a specific emotion would use a suitable vocabulary in the translation.”

This research builds on the authors’ previous work, which was the first to explore combining machine translation (MT) models with emotion information. Their earlier study demonstrated that adding emotion-related data to input sentences could enhance translation quality. In this latest study, Brazier and Rouas take the concept further by replacing the MT model used in their prior work with a fine-tuned LLM.

Source: https://slator.com/

Full article: https://slator.com/emotion-is-what-you-need-emotional-context-improves-translation-quality-of-llms/