Our Text-to-Speech (TTS) engine brings a natural, human-like voice to digital Somali content. By utilizing neural vocoders, we have developed voice synthesizers that capture the melodic patterns and intonations of native Somali speakers.
This technology is vital for making the web more accessible to visually impaired individuals and for creating interactive voice assistants. We are also collaborating with content creators to provide automated voiceovers for educational and news programming.
Our ASR (Automatic Speech Recognition) system is designed to provide highly accurate transcriptions of spoken Somali. This project leverages state-of-the-art deep learning architectures, trained on thousands of hours of speech data to ensure reliability across various accents and recording conditions.
The primary goal is to improve accessibility for Somali speakers, particularly those with disabilities, and to facilitate better human-computer interaction. The system is also being adapted for use in media monitoring and automated customer service platforms.