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 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 using deep learning

• Learn how to build AI text to speech system using gTTS

• Learn 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 text

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

• Learn 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 speech

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

• Learn how AI meeting transcriber and summarizer works starting from recording multi-speaker conversations, perform transcription, and then generate concise meeting summaries

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

• Learn how voice command recognition system works starting from analyzing audio input to detect commands, transcribing the speech, and mapping recognized phrases to predefined system actions

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

• Learn how to integrate AI models from Hugging Face library