Build an AI Assistant with ChatGPT and Voice Recognition

Build an AI Assistant with ChatGPT and Voice Recognition

Table of Contents

1. Introduction
2. Building a Chat Bot with ChatGPT API and Speech Recognition
3. Installing Required Libraries
4. Creating the Vivi Class
5. Initializing OpenAI ChatGPT
6. Generating Prompt Completions
7. Integrating Voice Assistant
8. Initializing Pyttsx3 and Speech Recognition
9. Implementing Speech Recognition
10. Adding Text-to-Speech Functionality
11. Saving Conversations

Building a Chat Bot with ChatGPT API and Speech Recognition

In this article, we will explore how to build a chat bot using the ChatGPT API and speech recognition. We will use the OpenAI API to generate prompt completions with the ChatGPT model and utilize speech recognition to enable voice interaction with the chat bot. By following this tutorial, You will learn how to set up the necessary libraries, Create a Vivi class for the chat bot, integrate voice assistant functionality, and save conversations for future reference.

Installing Required Libraries

Before getting started, make sure you have the following libraries installed:

• OpenAI: pip install openai
• Pyttsx3: pip install pyttsx3
• SpeechRecognition: pip install speechrecognition

Creating the Vivi Class

To build the chat bot, we will create a Vivi class. This class will contain all the necessary methods and functions for generating prompt completions and enabling voice interaction. We will also initialize the necessary components for the chat bot, such as the OpenAI API Key.

Initializing OpenAI ChatGPT

To initialize the OpenAI ChatGPT model, we will first need to set up the API key. You can obtain an API key from the OpenAI Website. Once you have the API key, set it as a variable in your code. Then, use the openai.chatcompletion.create method to create a completion for the ChatGPT model. Set the model as gpt-3.5-turbo and adjust the temperature parameter for the desired response randomness.

Generating Prompt Completions

To generate prompt completions, we will utilize the openai.ChatCompletion.create method. This method takes in the conversation history as input, which includes the system message and user message. By appending new user messages to the conversation, we can generate prompt completions Based on the chat bot's Context.

Integrating Voice Assistant

To enable voice interaction with the chat bot, we will need to utilize the Pyttsx3 library for text-to-speech functionality and the SpeechRecognition library for speech recognition. Initialize the text-to-speech engine and select a voice for the assistant. Also, initialize the microphone for speech input.

Implementing Speech Recognition

Implementing speech recognition involves listening to the user's voice input and converting it into text. We can utilize the speech_recognition.Recognizer class to achieve this. Set up the microphone as the audio source for speech recognition and adjust the energy threshold for optimal performance. Use a try-except block to listen for users' speech and retrieve the recognized text.

Adding Text-to-Speech Functionality

To provide responses in audio format, we will utilize the text-to-speech engine. Use the engine.say method to set the response text as input and use the engine.runAndWait method to play the response audio. By integrating the text-to-speech functionality, we can create a more immersive and interactive user experience.

Saving Conversations

To save conversations for future reference, we can implement a function that writes the conversation history to a text file. This function checks if the save folder path exists and creates a new text file with a suffix number to ensure no overwriting occurs. By saving conversations, we can analyze and review past interactions with the chat bot.

In conclusion, this article provides a step-by-step guide on how to build a chat bot using the ChatGPT API and speech recognition. By following the instructions and implementing the provided code snippets, you can create a fully functional chat bot with voice assistant capabilities. By saving conversations, you can analyze user interactions and improve the chat bot's performance over time.

Highlights:

• Build a chat bot with ChatGPT API and speech recognition
• Utilize the OpenAI API for prompt completions
• Enable voice interaction with the chat bot using Pyttsx3 and SpeechRecognition libraries
• Save conversations for future reference and analysis

FAQ:

Q: Can I use a different voice for the chat bot? A: Yes, you can select from the available voices in the Pyttsx3 library. Simply set the desired voice using the engine.set_voice method.

Q: Is it possible to train the chat bot with my own dataset? A: Currently, the ChatGPT model cannot be directly fine-tuned. However, you can use prompt engineering techniques and feedback loops to improve the chat bot's responses.

Q: Can I deploy the chat bot on a website or application? A: Yes, you can integrate the chat bot functionality into a website or application by utilizing the OpenAI API and appropriate frameworks/tools. Make sure to follow the usage and deployment guidelines provided by OpenAI.