本論文實現語音辨識及使用語音控制於兩輪平衡車，語音辨識系統使用基於TensorFlow之上執行的Keras完成，語音訊號利用梅爾頻率倒譜係數(Mel-Frequency Cepstral Coefficients, MFCCs)提取特徵值，並使用卷積類神經網路(Convolutional Neural Network, CNN)進行學習及建立模型。
兩輪平衡車使用Arm Cortex M0之微控制器實現，整體架構包含馬達、驅動電路、改變重心的機械結構及各類感測器。本論文採用比例、積分及微分控制器(Proportional-Integral-Derivative, PID)進行對兩輪平衡的控制，並以機械結構使重心改變達成兩輪平衡車前進或後退的功能。
本論文針對語音辨識系統架構修改進行實驗，挑選出正確率最高的架構應用於兩輪平衡車之控制中，最後實驗證實此論文的可行性。

This paper realizes a speech recognition system and voice control for a two-wheel balance vehicle. Based on TensorFlow, the speech recognition system is implemented by using Keras. The feature values of voice signals are extracted by using mel-frequency cepstral coefficients (1s), and then convolutional neural network (CNN) is used to learn and build a speech recognition model.
The control of the two-wheel balance vehicle is accomplished by an Arm Cortex M0 microcontroller. The overall architecture consists of a motor, a drive circuit, various types of sensors and a mechanical structure that changes the center of gravity of the two-wheel balance vehicle. This paper uses PID controller to control the balance of vehicles. And the mechanical structure makes the center of gravity change in order to make the two-wheeled balance vehicle move forward or backward.
This paper conducts some experiments on the modification of the speech recognition architecture, and selects the best recognition architecture to implement the voice control of the two-wheel balance vehicle. Finally, the experiment confirms the feasibility of the proposed method.

一、中文文獻
陳勁榮，” 兩輪移動平台影像追蹤控制與實現”，碩士論文，國立臺灣師範大學電機工程學系，台灣，2018
汪志宇，「兩輪移動車模糊控制」，碩士論文，國立台灣師範大學應用電子系，台灣，2012。

二、英文文獻
SEGWAY，From http://www.segway.com/
Kanchan Naithani, V. M. Thakkar and Ashish Semwal, “English Language Speech Recognition Using MFCC and HMM,”2018 International Conference on Research in Intelligent and Computing in Engineering ., San Salvador, Aug. 2018, Pages: 1 – 7.
Gunjan Jhawar , Prajacta Nagraj and P. Mahalakshmi, “Speech disorder recognition using MFCC,” 2016 International Conference on Communication and Signal Processing., Melmaruvathur, India, April 2016, Pages: 0246 – 0250.
Elvira Sukma Wahyuni, “Arabic speech recognition using MFCC feature extraction and ANN classification, ”2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering., Yogyakarta, Indonesia, Nov. 2017, Pages: 22 – 25.
Dyah Anggraeni, W. S. Mada Sanjaya, Madinatul Munawwaroh, M. Yusuf Solih Nurasyidiek , Ikhsan Purnama Santika, “Control of robot arm based on speech recognition using Mel-Frequency Cepstrum Coefficients (MFCC) and K-Nearest Neighbors (KNN) method,” 2017 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation., urabaya, Indonesia, Oct. 2017, Pages: 217 – 222.
Dhanny Wijaya Thiang, “Limited Speech Recognition for Controlling Movement of Mobile Robot Implemented on ATmega162 Microcontroller,” 2009 International Conference on Computer and Automation Engineering., Bangkok, Thailand, March 2009, Pages: 347 – 350.
Anup Kumar Paul, Dipankar Das, Md. Mustafa Kamal, “Bangla Speech Recognition System Using LPC and ANN ,” 2009 Seventh International Conference on Advances in Pattern Recognition., Kolkata, India, Feb. 2009, Pages: 171 – 174.
Du Guiming, Wang Xia, Wang Guangyan , Zhang Yan , Li Dan. “Speech recognition based on convolutional neural networks,” 2016 IEEE International Conference on Signal and Image Processing ,. Beijing, China, Aug. 2016, Pages: 708 – 711.
Untari N. Wisesty , Adiwijaya , Widi Astuti. “Feature extraction analysis on Indonesian speech recognition system,” 2015 3rd International Conference on Information and Communication Technology., Nusa Dua, Bali, May 2015, Pages: 54 – 58.
Kartiki Gupta, Divya Gupta. “An analysis on LPC, RASTA and MFCC techniques in Automatic Speech recognition system,” 2016 6th International Conference - Cloud System and Big Data Engineering., Noida, India, Jan. 2016, Pages: 493 – 497.
Yunsu, H. and Yuta, S., “Trajectory Tracking Control for Navigation of Self-Contained Mobile Inverse Pendulum,” IEEE/RSI/GI International Conference Advanced Robotic Systems and the Real World, Vol. 3, pp. 12-16, September 1994.
Grasser, F., D’Arrigo, A., Colombi, S. and Rufer, A. C., “JOE: A Mobile, Inverted Pendulum,” Transactions on Industrial Electronics, Vol. 49, No.1, pp. 107-114, February 2002.
Yeonhoon, K., Soo. K. and Yoon. K., “Dynamic Analysis of a Nonholonomic Two-Wheeled Inverted Pendulum Robot,” Journal of Intelligent and Robotic Systems﹐Vol.40, pp. 25-46, September 2005.
Jian-Xin Xu, Zhao-Qin Guo and Tong Heng Lee, “ Design and Implementation of a Takagi–Sugeno-Type Fuzzy Logic Controller on a Two-Wheeled Mobile Robot”. Ieee transactions on industrial electronics, VOL. 60, NO. 12, DECEMBER 2013
Wei An and Yangmin Li, “Simulation and Control of a Two-wheeled Self-balancing Robot”. IEEE International Conference on Robotics and Biomimetics (ROBIO) , Shenzhen, China, December 2013