本文選題：老年陪護機器人 + 神經(jīng)網(wǎng)絡(luò)��； 參考：《昆明理工大學(xué)》2017年碩士論文

【摘要】：近年來,隨著深度學(xué)習(xí)技術(shù)的高速發(fā)展,語音交互技術(shù)在很多行業(yè)領(lǐng)域得到了廣泛的應(yīng)用。但在現(xiàn)實環(huán)境中,由于干擾的存在,語音識別效果差,雖然語音交互軟件在市面上已普遍存在,但距離用戶廣泛接受還有一定的距離。面臨中國老齡化加劇現(xiàn)狀,目前我國增加了對老年人家用陪護機器人研發(fā)的投入,而且將其作為服務(wù)機器人領(lǐng)域發(fā)展的重要目標。本文利用集合語音分離、語音識別等技術(shù)為老年人設(shè)計了一款家用語音控制陪護機器人。本文在對基于深度神經(jīng)網(wǎng)絡(luò)的單通道語音分離系統(tǒng)仿真的基礎(chǔ)上,對語音分離的目標函數(shù),深度神經(jīng)網(wǎng)絡(luò)隱層數(shù)目以及激勵函數(shù)進行分析,提出一種適合用于漢語的語音分離系統(tǒng)模型,并實驗驗證了該系統(tǒng)對分離的有效性。在討論了基于深度神經(jīng)網(wǎng)絡(luò)的漢語孤立詞、非特定人語音識別的基礎(chǔ)上,使用基于MFCC與RASTA-PLP的組合特征在基于深度神經(jīng)網(wǎng)絡(luò)模型上進行語音識別仿真,分析了這種組合特征對語音識別正確率的影響。將語音分離與語音識別結(jié)合,構(gòu)建了陪護機器人語音交互控制系統(tǒng),采用JAVA編程設(shè)計了基于安卓的語音控制系統(tǒng),并分析一種通過語音控制的硬件系統(tǒng),通過語音控制機器人,實現(xiàn)人機交流,并驗證了陪護機器人語音交互控制系統(tǒng)的性能。本文針對老年人在使用陪護機器人過程中,尤其在有噪音干擾的情況下,容易造成識別不準確的問題,提供一種小詞匯量的非特定人、孤立詞語音識別系統(tǒng)模型,并實現(xiàn)對陪護機器人的控制。該系統(tǒng)也適合用于其他需要識別孤立詞的人機交互系統(tǒng),比如車載系統(tǒng)。
[Abstract]:In recent years, with the rapid development of deep learning technology, voice interaction technology has been widely used in many fields. But in the real environment, because of the existence of interference, speech recognition effect is poor. Although speech interactive software is widely available in the market, there is still a certain distance from widely accepted by users. Facing the aggravation of aging in China, our country has increased the investment in the research and development of the elderly household escort robot, and regarded it as the important goal of the development of the field of service robot. In this paper, a kind of home speech control escort robot is designed for the elderly by means of aggregate speech separation and speech recognition. Based on the simulation of single channel speech separation system based on deep neural network, this paper analyzes the objective function of speech separation, the number of hidden layers and the excitation function of the deep neural network. A speech separation system model suitable for Chinese is proposed, and the effectiveness of the system is verified by experiments. Based on the discussion of Chinese isolated words based on depth neural network and independent speech recognition, the speech recognition simulation based on the combination of MFCC and RASTA-PLP is carried out on the model of depth neural network. The influence of the combined features on the accuracy of speech recognition is analyzed. By combining speech separation with speech recognition, a speech interactive control system of escort robot is constructed. A speech control system based on Android is designed by JAVA programming. A hardware system based on speech control is analyzed, and the robot is controlled by voice. The man-machine communication is realized and the performance of the accompanying robot voice interactive control system is verified. In order to solve the problem of inaccurate recognition in the process of using accompanying robot, especially in the case of noise interference, this paper provides a small vocabulary model of isolated words speech recognition system. And realize the control of escort robot. The system is also suitable for other isolated word recognition systems, such as vehicular systems.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242

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