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A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology

机译：基于深度学习技术的缺陷患者基于语音指挥控制识别系统

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Yu-Yi Lin; Wei-Zhong Zheng; Wei Chung Chu; Ji-Yan Han; Ying-Hsiu Hung; Guan-Min Ho; Chia-Yuan Chang; Ying-Hui Lai;
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1. Speech-Input Speech-Output Communication for Dysarthric Speakers Using HMM-Based Speech Recognition and Adaptive Synthesis System [J] . Dhanalakshmi M., Celin T. A. Mariya, Nagarajan T., Circuits, systems, and signal processing . 2018,第2期

机译：基于HMM的语音识别和自适应合成系统的韵律演讲者的语音输入语音输出通信
2. Evaluating the feasibility and the potential efficacy of e-learning-based speech therapy (EST) as a web application for speech training in dysarthric patients with Parkinson's disease: a case study. [J] . Beijer LJ, Rietveld TC, Hoskam V, Telemedicine and e-health: the official journal of the American Telemedicine Association . 2010,第6期

机译：评估以电子学习为基础的言语治疗（EST）作为Web应用程序在患有帕金森氏病的重症患者中进行言语训练的可行性和潜在功效：一个案例研究。
3. Adaptive neuro-fuzzy inference system for evaluating dysarthric automatic speech recognition (ASR) systems: a case study on MVML-based ASR [J] . Asemi Adeleh, Salim Siti Salwah Binti, Shahamiri Seyed Reza, Soft computing: A fusion of foundations, methodologies and applications . 2019,第10期

机译：用于评估发育近似自动语音识别（ASR）系统的自适应神经模糊推理系统：基于MVML的ASR案例研究
4. Deep Learning of Articulatory-Based Representations and Applications for Improving Dysarthric Speech Recognition [C] . Feifei Xiong, Jon Barker, Heidi Christensen ITG-Symposium on Speech Communication . 2018

机译：基于发音的表示形式的深度学习及其在动态构音识别中的应用
5. Deep Learning Based Array Processing for Speech Separation, Localization, and Recognition [D] . Wang, Zhong-Qiu. 2020

机译：基于深度学习的语音分离，本地化和识别的阵列处理
6. Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features [O] . Tursunov Anvarjon, Mustaqeem, Soonil Kwon 2020

机译：深网络：使用深频特征的基于轻量级CNN的语音情感识别系统
7. Adaptive help for speech dialogue systems based on learning and forgetting of speech commands [O] . Er Hof, Eli Hagen, Er Huber 2006

机译：基于学习和忘记语音命令的语音对话系统的自适应帮助

A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology

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