创新的个人辅助:语音识别和NLP驱动的机器人原型

Michelle Valerie, I. Salamah, Lindawati
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引用次数: 0

摘要

本文介绍了一个具有高级语音识别和自然语言处理(NLP)能力的个人助理机器人原型的开发和评估。它由树莓派微处理器驱动,是机器人硬件的核心组件。它的设计目的是接收命令,并通过使用集成的语音识别和NLP技术,执行请求的动作,迅速做出反应。该样机旨在通过音频到文本的转换和高质量的图像捕获来提高会议效率和生产力。结果显示,该方法在印尼语和英语中的准确率分别为100%和99%。高效的处理速度,印尼语平均每分钟9.07秒,英语平均每分钟15.3秒,进一步增强了机器人的功能。此外,集成了一个高分辨率的网络摄像头,使1280 x 720像素的高质量图像捕获。实时集成谷歌驱动器,确保安全存储和无缝的数据管理。研究结果强调了原型在促进顺利互动和有效沟通方面的有效性,并利用NLP进行智能语言理解。集成基于nlp的语音识别、可视化文档和数据传输提供了一个管理音频、文本和图像数据的综合平台。本研究中提出的个人助理机器人原型代表了人机交互的重大进步,特别是在会议和协作工作环境中。NLP的进一步改进可以提高效率,促进无缝的人机交互体验。
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Innovative Personal Assistance: Speech Recognition and NLP-Driven Robot Prototype
This paper presents the development and evaluation of a personal assistant robot prototype with advanced speech recognition and natural language processing (NLP) capabilities. Powered by a Raspberry Pi microprocessor, it is the core component of the robot's hardware. It is designed to receive commands and promptly respond by performing the requested actions, utilizing integrated speech recognition and NLP technologies. The prototype aims to enhance meeting efficiency and productivity through audio-to-text conversion and high-quality image capture. Results show excellent performance, with accuracy rates of 100% in Indonesian and 99% in English. The efficient processing speed, averaging 9.07 seconds per minute in Indonesian and 15.3 seconds per minute in English, further enhances the robot's functionality. Additionally, integrating a high-resolution webcam enables high-quality image capture at 1280 x 720 pixels. Real-time integration with Google Drive ensures secure storage and seamless data management. The findings highlight the prototype's effectiveness in facilitating smooth interactions and effective communication, leveraging NLP for intelligent language understanding. Integrating NLP-based speech recognition, visual documentation, and data transfer provides a comprehensive platform for managing audio, text, and image data. The personal assistant robot prototype presented in this research represents a significant advancement in human-robot interaction, particularly in meeting and collaborative work settings. Further refinements in NLP can enhance efficiency and foster seamless human-robot interaction experiences.
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