Build Talking AI ChatBot with Text-to-Speech using Python!

Summary

This video script outlines the creation of an AI speech bot using AssemblyAI, 11Labs, and OpenAI. It details the process of setting up Python libraries, obtaining API keys, and implementing real-time speech-to-text transcription with AssemblyAI. The script then explains how to use OpenAI's GPT-4 for generating responses to questions and 11Labs for converting text into audio. The tutorial concludes with a test of the application, suggesting potential extensions like multimodal integration and website deployment.

Takeaways

• 🌟 The capital of New Zealand is Wellington.
• 🤖 Overfitting in machine learning refers to a model learning the training data too well, which can negatively impact its performance on new data.
• 🛠️ The video demonstrates creating an AI speech bot using AssemblyAI, 11Labs, and OpenAI.
• 📚 It's necessary to download specific Python libraries: AssemblyAI, 11Labs, and OpenAI for the project.
• 🔑 API keys for AssemblyAI and OpenAI need to be set up for the bot to function.
• 🎙️ AssemblyAI is used for real-time speech-to-text transcription.
• 🗨️ OpenAI GPT-4 is utilized to generate responses to questions based on the transcript.
• 🔊 11Labs is employed to convert the text responses from OpenAI into audio format.
• 🔄 The 'on data' function captures and stores full sentences for processing by OpenAI's API.
• 🛑 The 'on error' function handles any errors that occur during real-time transcription.
• 🔄 The 'handle conversation' function orchestrates the transcription, response generation, and audio playback.
• 📝 The response from OpenAI is parsed to extract the main content, which is then converted to audio using 11Labs.
• 📺 The video suggests potential extensions, such as deploying the bot on a website or making it multimodal to handle images and videos.

Q & A

What is the capital of New Zealand?

The capital of New Zealand is Wellington.

What does overfitting mean in the context of machine learning?

Overfitting in machine learning refers to a model's tendency to learn the training data too well, to the extent that it negatively impacts the model's performance on new, unseen data.

What are the two main Python libraries mentioned in the script for creating the AI speech bot?

The two main Python libraries mentioned in the script are AssemblyAI and OpenAI.

What is the purpose of the 'on_data' function in the script?

The 'on_data' function handles the responses from the AssemblyAI API, providing real-time transcription of spoken words into text.

What does the 'on_error' function in the script do?

The 'on_error' function is designed to handle any errors that may occur during the real-time transcription process.

What is the role of the 'handle_conversation' function in the script?

The 'handle_conversation' function is responsible for creating a transcriber object that handles real-time transcription, and subsequently passing the transcript to the OpenAI API to generate a response.

Why is the response from OpenAI limited to 1,000 characters?

The response from OpenAI is limited to 1,000 characters to ensure faster processing. However, this limit can be adjusted if a longer response is desired, albeit at the cost of increased processing time.

How is the main content extracted from the nested JSON response of the OpenAI API?

The main content is extracted using a specific line of code that parses the nested JSON structure and stores the desired text into a variable.

What is used to generate audio from the text response in the script?

Eleven Labs is used to generate audio from the text response obtained from the OpenAI API.

Which voice is specified for the audio generation in the script?

The voice of Bella is specified for audio generation in the script.

What additional functionalities can be built on top of the AI speech bot as suggested in the script?

Additional functionalities that can be built on top of the AI speech bot include deploying it onto a website and making it multimodal to take in images and videos.