International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
AI BASED VOICE ASSISTANT Shejal Devkar1, Jagruti Patil2, Akhil Naskar3, Rakesh Singh4 B.E. Students Department of Computer Engineering G. V. Acharya Institute of Engineering and Technology, Shelu, Dist-Raigad, Maharashtra, India-410201
---------------------------------------------------------------------***--------------------------------------------------------------------settings, and to-do list creation through voice or text Abstract - This desktop voice assistant initiative commands. It requires activation phrases to engage its leverages Python’s AI capabilities to offer an listening feature, followed by the user’s instructions. This interactive experience through vocal interactions. The voice assistant is tailored for optimal use across all user endeavor encompasses crafting a voice assistant demographics, enhancing productivity by handling routine rooted in Python that is adept at executing an array of tasks and fetching online information. Historically, ‘virtual functions such as activating alarms, providing assistants’ referred to web-based service providers; meteorological updates, dispatching electronic mails, however, today’s voice assistants are distinct, focusing on streaming melodies, among others. Engineered for three core functions: converting text to speech, optimal intuitiveness and accessibility, the assistant interpreting text for intent, and translating intent into boasts a streamlined interface that facilitates seamless action. Our voice assistant is under continuous development to expand its capabilities. Unlike virtual communication via spoken language instructions. The assistants who are human contractors, voice assistants are project harnesses AI-driven voice recognition automated systems that proactively fulfill our needs, all technologies, ensuring precise comprehension and thanks to advancements in AI-driven voice technology. execution of user directives. 2. Literature Survey
To actualize the voice assistant’s capabilities, the project employs a suite of Python libraries. Speech Recognition is deployed for translating spoken words into written text, while PyAudio handles the auditory inputs and outputs. Text-to-speech conversion is managed by gTTS, and audio file playback is orchestrated using the play sound library.
The manuscript commences with an exposition on voice assistants, charting their ascent to prominence in the digital age. It traces the lineage of these systems from the nascent IBM Shoebox to contemporary incarnations like Siri, Google Assistant, and Alexa. Subsequently, the document delves into the architecture of voice assistant systems, dissecting elements such as speech recognition, natural language processing, dialogue orchestration, and speech generation. It elucidates the array of methodologies and computational frameworks that underpin each component, appraising their efficacies and constraints.
Key Words: Voice , Assistant , Static , Text , Speech
1.INTRODUCTION In an era where efficiency is paramount, the advent of intelligent home automation and IoT devices has sparked a demand for solutions that streamline everyday activities. Addressing this need, virtual assistants have emerged as AI-driven facilitators, enabling users to orchestrate their tasks and manage smart devices through conversational language. This project introduces a desktop voice assistant built on Python, designed to enhance user interaction with their computers in a frictionless and effective manner.
The discourse culminates in the presentation of a voice assistant, conceived through Python and AI, capable of interpreting and executing user-issued directives. Employing NLP, the assistant translates vocal or textual inputs into operative commands, thereby streamlining processes and conserving time. In recent years, AI-based voice assistant systems have garnered significant attention due to their potential to revolutionize human-computer interaction. These systems utilize artificial intelligence techniques to understand and respond to user queries and commands via natural language. This literature survey aims to explore the advancements, challenges, and future directions in the field of AI-based voice assistant systems.
The system is crafted using a variety of Python libraries, encompassing speech recognition, natural language processing, and text-to-speech modules, to forge a virtual assistant that is both reactive and approachable. Interaction with the assistant is voice-driven, empowering users to accomplish tasks such as scheduling reminders, web searching, audio playback, and email composition effortlessly. The software serves as a digital aide, streamlining tasks like weather forecasts, reminder
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