AI Text To Speech
Hey there! Filip from Inworld here. Are you curious about pulling dynamic data on-the-fly into an Unreal project? Stick around as I walk you through integrating external data sources with Inworld AI characters, using entities, parameters, and goals. We'll see a character come to life by fetching and sharing real city populations based on user prompts.
Learning the ropes of Unreal starts with setting up our Inworld studio goals and entities. Here, we focus on the 'population of City' intent and how simple training phrases, devoid of city names, get completed with the 'City' entity. This setup allows the AI to match our query with known synonyms, preparing it to fetch the right data.,Entities work as the glue between our AI's understanding and the user's query. Each city in the 'City' entity, such as San Francisco or New York, gets linked to a specific action—triggering our AI to retrieve corresponding data from an external URL.,When our AI recognizes a city name, it activates the 'get population' goal. This sends a trigger, paired with parameters, down the line. Next, we'll see how this setup unfolds within Unreal, making dynamic data retrieval not just possible, but incredibly streamlined.
Transitioning from Inworld studio to Unreal Engine, the integration process starts to take shape with goal showcases in the playground's demo. PinkBot, a character equipped with the BP data retrieval component, illustrates how the 'City' entity and HTTP requests are configured in Unreal.,Using Unreal's Blueprint visual scripting system, we attach an event listener to the Inworld character's triggers. The system then switches based on the received trigger, processes the GET request for the targeted city, and parses the returned data to retrieve the population figure.,After fetching the population data via HTTP request, we close the loop by sending the 'provide population' trigger. This instructs our AI character to communicate the retrieved data to the player, showcasing the finishing touches of a dynamic, responsive Unreal project.
The community voice reveals a keen interest in seeing similar demonstrations of dynamic data retrieval using Unity. The adaptability of these concepts to other platforms highlights the broad applicability and value of the method discussed.,By exploring how to apply these techniques in Unity, we could open doors for developers who are more familiar with or prefer Unity's ecosystem, increasing accessibility and fostering cross-platform innovation.,The curiosity about Unity implementations reflects the desire for understanding transferable skills, ensuring that knowledge gained from one engine can illuminate paths in another, enriching the developer's toolkit.
Feedback from the audience points to the importance of audio quality, especially text-to-speech engines, when it comes to fresh, cutting-edge technology demonstrations.,A top-notch text-to-speech engine can augment the immersive experience, make content more engaging, and avoid the pitfall of new tech being perceived as outdated due to subpar audio elements.,Improving the auditory component aligns with creating a more holistic and contemporary demonstration, thereby supporting the audience in appreciating the full potential and sophistication of the technology presented.
In this article, we delve into the art of dynamic data retrieval within Unreal Engine. Utilizing entities and parameters underpinned by carefully crafted goals, you can command an Inworld AI character to respond with data fetched in real-time from an external source. From querying city populations to demonstrating the process in Inworld studio and Unreal, we cover the essentials, offering a glimpse of the seamless integration in action.
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Unreal Speech utilizes advanced AI technology to convert text into realistic and natural-sounding speech.
For information on free trials, please visit the official website: https://unrealspeech.com/
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