This code implements an interactive voice-to-text converter and AI response generator within a Google Colab environment, allowing users to engage with an AI model in a dynamic manner. The primary functionality is provided by utilizing the transformers library, which loads the GPT-2 model for text generation. The code integrates JavaScript to access the browser’s speech recognition capabilities, enabling users to convert spoken language into text seamlessly.
Upon running the code, users can initiate voice recognition by clicking the "Start Recording" button, which triggers a JavaScript function to begin capturing audio input. Once the user stops the recording, the recognized text is displayed on the webpage. If users prefer to input text directly, they can type their queries or prompts into a dedicated text box.
The core of the interaction lies in the "Generate Response" button, which, when clicked, activates a Python function that checks for either recognized voice input or manually entered text. This function utilizes the GPT-2 model to generate a response based on the available input. The AI-generated response is then displayed in a separate output area, allowing users to see the results of their queries.
This setup caters to different user preferences, providing flexibility in how they choose to communicate with the AI—whether through spoken words or typed text. The user interface is designed to be intuitive, with clear instructions and visual feedback. Overall, this code enhances accessibility to AI-driven conversations, making it a valuable tool for educational purposes, interactive applications, and personal experimentation in natural language processing. By merging voice recognition and text input, it demonstrates the potential for creating engaging and responsive AI systems that adapt to user needs.