In this project, we confront the linguistic barriers faced by Yoruba speakers due to limited language resources. Image generation models primarily excel with English prompts, posing a challenge for non-English speakers. To address this, we embarked on a dual-track approach: data collection and model development. Firstly, recognizing the scarcity of Yoruba datasets, particularly in image generation prompts, we meticulously curated our own dataset. English sentences were carefully selected to serve as image generation prompts and then translated into Yoruba using a dictionary-based approach. Next, we developed a custom translator model trained specifically to translate Yoruba into English. This intermediary step ensures seamless integration with image generation models, allowing for smoother operation and accurate results. Through rigorous testing, we achieved an impressive 85% accuracy on the test set, affirming the efficacy of our approach. The core strength of our project lies in its ability to empower users to generate images in their native language without encountering language barriers. By collecting our own data and training custom models, we circumvent the limitations imposed by the scarcity of Yoruba resources. Leveraging the SDXL API for image generation further enhances the user experience, ensuring high-quality outputs. Looking ahead, we envision extending our efforts to include additional languages such as Fon and Dendi, expanding our dataset and catering to a broader audience. Furthermore, our ultimate goal is to develop a model capable of directly generating images from Yoruba, Fon, and Dendi without the need for translation into English. In summary, our project not only addresses a pressing need within the Yoruba-speaking community but also lays the groundwork for future advancements in multi-lingual image generation. Through our innovative approach, we pave the way for inclusive, barrier-free communication and creative expression.
1. Optimised Prompt based on User's reuirement with simplicity and precision. User are asked to fill the answer based on the default questions like goals , interest and challenges faced, based on the mentioned criteria. Solution: It will be a prompt that gets generated along with the solution that is provided based on the tailored prompt. 2. In built AI application for Brainstorming - The AI will directly interact based on the prompt, it will be more refined and video link is also added. 3. Providing additional features like youtube links that are related to the topic of discussion - For every prompt answered, there will be a youtube link. Why you ask? We understood the Customer pain point where we felt that for certain propts for example: cooking having a video along with the videos would really help the customers to work on this with ease and confidence. 4. How does this bring value as a product and business: a) As a product - To provide an assistance for any kind of AI tools: as AI is available, but the instructions required to prompt the AI is not available. This is where Volund comes in. Avoiding reprtition prompts and instructions saving time and effort with additional links always helps in providing a good experience. b) As a business - We are able to include a large number of potential users that have not been included and building AI.With a growing market in AI, the dependency on right prompt with becomes very important to understand the intention of the user who is looking for solutions.
Chorus is an AI voice partner designed to empower vocally impaired individuals, enabling them to communicate with confidence. The problem weโre focused on solving is democratizing access to a speech pathologist healing emotional trauma from a vocal injury receiving feedback without paying large amounts of money. GPT4o allows vocal comprehension in tandem with Whisper and TTS. I built Chorus to help vocally impaired people progress and speak confidently through AI-assisted voice rehab. This is a personal problem for me, as I've had surgery to remove benign tumors from my vocal cords when I was 13, and had to teach myself how to speak again from scratch. NGL the experience was emotionally painful and I think younger me would've loved a guide to speak to 1 on 1.