Welcome to the overview video for the project; Create a Voice Assistant with Open AI's GPT-3 and IBM Watson. By the end of this project, you'll be able to obtain the following objectives: explore chatbots and their applications, set up an environment using Python to build chatbots, acquire skills to integrate an LLM to infuse intelligence in a chatbot, implement Watson speech to text and text to speech functionalities, and create a functioning voice-enabled AI assistant.
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Need for voice-based assistants
The domain of voice-based AI is rapidly transforming how we interact with the technology. One particular promising application lies in intelligent voice assistants. Consider a busy professional rushing to design a presentation. With their hands occupied, they can't access their computer for a quick search.
However, a voice query to the AI assistant, "Summarize the key trends of use of AI in electric cars," allows them to stay informed and productive. Voice AI-based assistants enable you to seamlessly engage in natural conversations, access information, and find answers all through the power of your voice.
Creating a voice assistant
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| Creating a voice assistan |
In this project, we will create a voice assistant using Open AI's GPT-3 model and IBM Watson Embeddable AI. The GPT-3 model will enable the assistant to understand and respond to user input.
The Watson Speech To Text, or STT, empowers the assistant to hear and understand a user's response. Watson Text To Speech, or a TTS enables the assistant to read the answers back to the user.
IBM Watson contains speech libraries for Embed, a set of containerized text to speech and speech to text libraries that help to respond to human speech, process data, and answer questions that help individuals and companies respond to their problems.
Introduction to the project
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| Introduction to the project |
This project explores chatbots and their applications. You will create a functioning assistant with a high intelligence level that will take voice input and provide a spoken response.
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| Project: Create a chatbot |
Demo of the voice assistant
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| Demo of the voice assistan |
Let's check out a demo of the voice assistant you'll develop in this project. The interface of the assistant displays the title, Voice Assistant. It provides a feature to toggle between light and dark modes. This assistant works with both text and voice. Prompt your questions by typing in the message field or by clicking the recorder icon to speak. For example, what are Shakespeare's tragedies? The assistant provides a detailed response, displaying the text and playing an audio response, showcasing the text to speech integration. Continue the conversation by typing or using the recorder option. To conclude, prompts like no and thank you, help wrap up interactions with your assistant.
What does the project include?
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| Including in the project |
To build the voice assistant, you will construct the interface using HTML, CSS, and JavaScript that communicates with the assistant. For building the back end, you will use Python and Flask. Flask is a web framework for building web applications. In the project, Flask is supported by Docker to create containers that manage the dependencies.
This is followed by integrating IBM Watson speech to text functionality to enable the chatbot to understand voice input from a user.
Next, you will integrate GPT-3 for infusing intelligence into the chatbot. Further, you will integrate Watson text to speech to give the chatbot a voice for spoken responses.
Once all components are combined, you will develop a functioning voice assistant that can take both text and voice input and provide both text and spoken responses.
Prerequisites
To work on this project, you should be familiar with Python and Flask. Also, it is recommended, but not essential, to have a basic knowledge of HTML, CSS, and JavaScript. The project provides step by step instructions on how to work with the code and the different activities required to build the chatbots using AI tools.
Learning objectives
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| Learning objectives from the project |
By the end of this project, you'll be able to obtain the following objectives: explore chatbots and their applications, set up an environment using Python to build chatbots, acquire skills to integrate an LLM to infuse intelligence in a chatbot, implement Watson speech to text and text to speech functionalities, and create a functioning voice-enabled AI assistant.
Get ready for the project
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| Get ready for building an AI assistant |
This project will dive deep into building a powerful assistant. You'll learn about chatbots and web development with Flask and Python. You will also integrate GPT-3 and IBM Watson capabilities to build an assistant with speech recognition. By the end, you will have created a fully functional AI assistant that showcases your new found expertise working with LLMs using APIs.
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