A Research Synthesis on Conversion of Text to Gloss Language

The research community has begun to look for text- to-speech technologies that go beyond traditional language or text interpretation expectations. A new method has emerged that uses the power of auditory models to improve the accuracy and efficiency of text-to-dictionary conversion, making it more efficient in natural language processing and deep learning.Text-to-gloss conversion is the process of transforming written or spoken text into a standardized gloss format, which represents linguistic elements in a structured and concise manner. It is primarily used in linguistics and language documentation to analyze grammar, syntax, and linguistic structures systematically. Text-to-gloss conversion benefits deaf individuals by providing a visual representation of spoken language, aiding in sign language learning, creating accurate captions, enhancing communication, and supporting education. It makes spoken language more accessible and understandable, bridging the gap between auditory and visual communication for the deaf community. This research explores the emerging field of using auditory models for text-to-gloss conversion and presents a case study.