# NeuralNetX AI Products ## Text to Image It has the ability to transform text-based descriptions into realistic images using advanced GAN (Generative Adversarial Network) algorithm. This module transforms texts processed by NLP (Natural Language Processing) methods into photo-realistic images using a neural network. The GAN algorithm can produce authentic and realistic images, taking into account detailed styles and features. ## Text to Video Creates compelling videos based on text-based descriptions. This module combines GAN (Generative Adversarial Network) and language modeling techniques to transform text into video content. Using advanced artificial intelligence algorithms, scenarios are created with text-based descriptions and videos are produced automatically. ## Text to Audio It automatically converts the text to an audible shape. This module works with deep learning and natural language processing methods. It takes text-based descriptions and uses voice synthesis algorithms to produce a natural voice narration. As a result, users can automatically announce texts in audio format and create audio recordings in different languages ​​and intonations. ## Chat with AI It allows users to interact with artificial intelligence on a text-based basis. This module uses NLP (Natural Language Processing) techniques and powerful language models. Users can chat with the AI ​​model with text-based inputs, ask questions and get real-time text-based responses. ## Chat with AI It allows users to interact with artificial intelligence on a voice-based rather than text-based basis. This module analyzes the user's voice input using automatic speech recognition (ASR) and natural language processing (NLP) algorithms. It understands voice commands, generates responses and provides voice feedback to the user. In this way, users can experience a real voice-based chat experience with artificial intelligence. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://neuralnetx.gitbook.io/litepaper/neuralnetx-ai-products.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.