Building Ai Text To Speech & Speech To Text With Python

Building AI speech to speech translation, AI meeting transcriber & summariser, and voice command recognition system

What you'll learn

Learn how to build AI text to speech system using gTTS

Learn how to build AI speech to text system using Open AI Whisper

Learn how to build AI speech to speech translation system using NLP

Learn how to build AI meeting transcriber and summarizer system using DeepSeek

Learn how to build voice command recognition system for smart home automation simulation

Learn the basic fundamentals of AI text to speech synthesis and automatic speech recognition, such as getting to know their use cases and technical limitations

Learn how AI text to speech system works starting from converting written text into phonemes and acoustic features, then generating realistic human like voice

Learn how AI speech to text system works starting from capturing raw audio waveforms, then extracting features like MFCCs and using models like Open AI Whisper

Learn how AI speech to speech translation system works starting from recognizing input in the source language, translating it using NMT, synthesizing the speech

Learn how AI meeting transcriber and summarizer works starting from recording multi-speaker conversations, perform transcription, generate meeting summary

Learn how a voice command recognition system works by analyzing audio input, transcribing speech, and triggering predefined actions based on recognized phrases

Learn how to integrate AI models from Hugging Face library

Requirements

No previous experience in artificial intelligence automation is required

Basic knowledge in Python

Description

Welcome to Building AI Text to Speech & Speech to Text with Python course. This is a comprehensive project based course where you will learn how to build advanced AI voice based systems, including speech synthesis, transcription, translation, summarization, and voice command recognition. This course is a perfect combination between artificial intelligence automation and Python, making it an ideal opportunity to practice your programming skills while improving your technical knowledge in software development. In the introduction session, you will learn the basic fundamentals of AI text to speech synthesis and automatic speech recognition, such as getting to know their use cases and technical limitations. Then, in the next section, you will learn how to import AI models from Hugging Face, it is a platform that offers a diverse selection of pre-trained large language models and they are ready to use. Afterward, we will start the project section. In the first project, we are going to build AI text to speech system using gTTS and Gradio. This system will enable users to convert any given text into speech and download the audio file in just one click. In the second project, we are going to build AI speech to text system using OpenAI Whisper. This system will facilitate users to either record their voice or upload an audio file, which will then be converted into text automatically. Meanwhile, in the third project, We are going to build AI speech to speech translation using transformers and NLP models. This system will allow users to speak in English, and within a few seconds, the speech will be translated into Spanish in audio form. Following that, in the fourth project, we are going to build AI meetings transcriber and summarizer using DeepSeek. This system will enable users to upload a meeting recording, and AI will automatically transcribe the audio and summarize the key points from the meeting. Then, in the fifth project, we are going to build a voice command recognition system for smart home automation. This system will allow users to control the room temperature, turn on or off the air conditioner, heater, and lights using voice commands, simulating a smart home automation dashboard and we will design the user interface using Gradio. Lastly, at the end of the course, we will conduct testing to make sure each system has been fully functioning and all logics have been implemented correctly.Before getting into the course, we need to ask this question to ourselves. Why should we build AI text to speech and voice recognition systems? Well, here is my answer, These technologies are incredibly useful as they enable seamless, hands-free interactions, which can improve user experiences and streamline business operations across a wide range of industries. In sectors like customer service, education, healthcare, and entertainment, voice recognition systems can enable efficient communication, automate customer support, assist in transcribing medical records, and even enhance accessibility for people with disabilities. Building these projects will equip you with valuable skills and knowledge in AI and natural language processing, which are in high demand in the tech industry. With these capabilities, you will be able to build your own AI apps, turn your innovations into AI products, and stay competitive in the rapidly evolving digital landscape.Below are things that you can expect to learn from this course:Learn the basic fundamentals of AI text to speech synthesis and automatic speech recognition, such as getting to know their use cases and technical limitationsLearn how AI text to speech system works starting from converting written text into phonemes and acoustic features, then generating realistic human like voice using deep learningLearn how to build AI text to speech system using gTTSLearn how AI speech to text system works starting from capturing raw audio waveforms, then extracting features like MFCCs and using models like Whisper to transcribe audio into textLearn how to build AI speech to text system using Open AI WhisperLearn how AI speech to speech translation system works starting from recognizing spoken input in the source language, translating it using a neural machine translation model, and finally synthesizing the translated speech with text to speechLearn how to build AI speech to speech translation system using NLPLearn how AI meeting transcriber and summarizer works starting from recording multi-speaker conversations, perform transcription, and then generate concise meeting summariesLearn how to build AI meeting transcriber and summarizer system using DeepSeekLearn how voice command recognition system works starting from analyzing audio input to detect commands, transcribing the speech, and mapping recognized phrases to predefined system actionsLearn how to build voice command recognition system for smart home automation simulationLearn how to integrate AI models from Hugging Face library

Overview

Section 1: Introduction to the Course

Lecture 1 Introduction

Lecture 2 Table of Contents

Lecture 3 Whom This Course is Intended for?

Section 2: Tools, IDE, and Hugging Face

Lecture 4 Tools, IDE, and Hugging Face

Section 3: Introduction to AI Text to Speech & Speech to Text

Lecture 5 Introduction to AI Text to Speech & Speech to Text

Section 4: How AI Text to Speech System Works?

Lecture 6 How AI Text to Speech System Works?

Section 5: Building AI Text to Speech System with gTTS

Lecture 7 Building AI Text to Speech System with gTTS

Section 6: Testing AI Text to Speech System

Lecture 8 Testing AI Text to Speech System

Section 7: How AI Speech to Text System Works?

Lecture 9 How AI Speech to Text System Works?

Section 8: Building AI Speech to Text System with Open AI Whisper

Lecture 10 Building AI Speech to Text System with Open AI Whisper

Section 9: Testing AI Speech to Text System

Lecture 11 Testing AI Speech to Text System

Section 10: How AI Speech to Speech Translation System Works?

Lecture 12 How AI Speech to Speech Translation System Works?

Section 11: Building AI Speech to Speech Translation System with NLP

Lecture 13 Building AI Speech to Speech Translation System with NLP

Section 12: Testing AI Speech to Speech Translation System

Lecture 14 Testing AI Speech to Speech Translation System

Section 13: How AI Meeting Transcriber & Summarizer System Works?

Lecture 15 How AI Meeting Transcriber & Summarizer System Works?

Section 14: Building AI Meeting Transcriber & Summarizer System with DeepSeek

Lecture 16 Building AI Meeting Transcriber & Summarizer System with DeepSeek

Section 15: Testing AI Meeting Transcriber & Summarizer System

Lecture 17 Testing AI Meeting Transcriber & Summarizer System

Section 16: How Voice Command Recognition System Works?

Lecture 18 How Voice Command Recognition System Works?

Section 17: Building Voice Command Recognition System for Smart Home Automation Simulation

Lecture 19 Building Voice Command Recognition System for Smart Home Automation Simulation

Section 18: Testing Voice Command Recognition System

Lecture 20 Testing Voice Command Recognition System

Section 19: Conclusion & Summary

Lecture 21 Conclusion & Summary

Software developers who are interested in building voice based AI apps,IoT engineers who are interested in integrating voice command recognition system to their devices