What you will learn
- Use speech recognition and voice synthesis libraries to build a complete virtual assistant
- Read tasks from an Excel file
- Search for specific terms in the web browser
- Predict emotions by speech
- Listen and recognize speech from the microphone
- Create and read reminders from text files
Requirements
- Programming logic
- Basic Python programming
Description
Virtual assistants are already a reality in our daily lives, performing many tasks that make our day to day easier. Some examples are: creating and reading calendar reminders, searching the Internet, playing our favorite songs, speaking the weather forecast, reading the news and even telling jokes. The best known assistants today are Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa and Google Assistant.
In this step-by-step course you are going to learn how to build your own virtual assistant that works with voice commands! You will learn how to use speech recognition and voice synthesis libraries, so that the assistant understands what you say and also speaks the appropriate responses. Below are some features that will be implemented:
- Web browser searches by voice
- Classification of emotions in your voice (sadness, surprise, disgust, neutral, fear, happiness, and calm)
- Open specific Youtube videos according to your emotion
- Recognize the voice from the microphone
- Date and time reading
- Create and read reminders from .txt files
- Excel file schedule reading
All codes will be implemented step by step using Python programming language and PyCharm IDE with the use of many different libraries, such as: playsound, SpeechRecognition, pyttsx3, tensorflow, librosa and openpyxl. We hope you enjoy the course and have a lot of ideias on how to apply the content on your own projects!
Who this course is for
- Beginners in the area of virtual assistants
- People interested in Natural Language Processing
- Undergraduate and graduate students who are taking subjects on Artificial Intelligence
- Data Scientists who want to grow their project portfolio
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