鲁棒实时自动语音命令基于树莓派的援助残疾人

A. Mnassri, Sihem Nasri, Mohamed Boussif, A. Cherif
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引用次数: 0

摘要

助行器被行动不便的人广泛使用。利用生理信号设计人机界面(hmi)来改善对机械移动设备(主要是轮椅)的控制,目前正在进行大量的研究工作。在一个合适的人机界面上通过生理学产生精确的控制命令是一个真正的挑战,因为严重残疾的人无法控制传统的轮椅。在此背景下,本工作开发了一种新的语音信号控制系统,以满足这些肢体残疾人群的需求。本系统分为两部分:第一部分是语音信号的识别、处理和分类,其中结合相对频谱感知线性预测(RASTA-PLP)和离散小波变换(DWT)对语音特征进行处理和提取,第二部分是机械采集模块,即电机驱动电路控制轮椅。用于实时录音的麦克风服务器。使用带有Linux操作系统内核的树莓派作为处理器。为了使处理器更加人性化和可靠,轮椅集成了语音接收模式。该模型在清洁环境下的平均识别率为100,在噪声环境下的平均识别率为80 ~ 100。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Real-time Automatic Voice Command based on Raspberry pi for assistance disabled people
Walkers are widely used by people with limited mobility. Much research work is underway to design human-machine interfaces (HMIs) using physiological signals to improve the control of mechanical mobility devices, mainly wheelchairs. Generating exact control commands through physiology in a suitable HMI is a real challenge because severely disabled people cannot control classic wheelchairs. In this context, this work develops a new voice-signal control system to meet the needs of this physically disabled population. This system is divided into two parts: part one covers the recognition, processing and classification of speech signals in this part the relative spectral-perceptual linear prediction (RASTA-PLP) and discrete wavelet transform (DWT) are combined to process and extract speech features and the second part includes the mechanical collection module, i. e. the wheelchair control by a motor drive circuit. The microphone servers for real-time voice recording. A Raspberry-Pi with a Linux operating system kernel is used as the processor. In order to make the processor more user-friendly and reliable, Voice-received mode is integrated into the Wheelchair. The model works successfully with an average recognition of 100 in clean environment and between 80 and 100 in noisy environment.
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