MERaLiON-AudioLLM: Bridging Audio and Language with Large Language Models
It addresses accessibility and usability in complex, multilingual environments for Singapore, but is incremental as it adapts existing methods to a new regional context.
The paper tackles the challenge of processing Singapore's multilingual and multicultural audio and language data by introducing MERaLiON-AudioLLM, a speech-text model that improves speech recognition and task-specific understanding for local accents and dialects.
We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning in One Network), the first speech-text model tailored for Singapore's multilingual and multicultural landscape. Developed under the National Large Language Models Funding Initiative, Singapore, MERaLiON-AudioLLM integrates advanced speech and text processing to address the diverse linguistic nuances of local accents and dialects, enhancing accessibility and usability in complex, multilingual environments. Our results demonstrate improvements in both speech recognition and task-specific understanding, positioning MERaLiON-AudioLLM as a pioneering solution for region specific AI applications. We envision this release to set a precedent for future models designed to address localised linguistic and cultural contexts in a global framework.