Abhay Kumar Pandit,
Saurav Kumar,
Manisha Sharma,
- Student HMR Institute of Technology and Management, New Delhi, India
- Student HMR Institute of Technology and Management, New Delhi India
- Associate Professor HMR Institute of Technology and Management, New Delhi, India
Abstract
With their ability to use natural language processing to enable hands-free technological engagement, voice assistants have become an indispensable aspect of modern living. This paper describes how to create a voice assistant with the Python programming language by utilizing its powerful libraries and frameworks for task automation, speech recognition, and natural language processing. The system architecture makes use of several Python modules, including PyAudio, NLTK (Natural Language Toolkit), and Speech Recognition, to process audio and interpret user inputs effectively. One of the hottest subjects in the modern world is voice assistants, commonly referred to as voice-based artificial intelligence (AI). These are programs that listen to human vocal instructions and reply, allowing for human-computer or device connection. These days, voice assistants are widely available and highly helpful in these hectic times. Due to the global epidemic that has forced people to use smartphones, voice assistants have become ubiquitous today, with Google Assistant being the most widely used. Even 5-year-old children can use it. Alexa from Amazon is a formidable competitor to Google Assistant and can do a wide range of tasks, from providing entertainment to controlling the Internet of Things (IoT) devices in homes. One of its best qualities is that it will benefit those with physical disabilities as well. For instance, those who are unable to walk can use the Internet of Things function to maintain and run household appliances. Thus, we usually try to create a voice assistant that is as user-friendly as the other voice assistants that are popular right now.
Keywords: Voice Assistant, Speech Recognition, Text-to-Speech, Internet of Things, Python
[This article belongs to Current Trends in Signal Processing(ctsp)]
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References
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Current Trends in Signal Processing
| Volume | 14 |
| Issue | 01 |
| Received | May 31, 2024 |
| Accepted | June 3, 2024 |
| Published | June 15, 2024 |