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请高手帮忙修改一下,毕业论文的摘要。在线等待,非常感谢 [Copy link] 中文

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Post time 2008-1-11 23:00:55 |Display all floors
ABSTRACT
The paper mainly studies on the technology of speech command recognition based on aerocraft in the aerial domain. The  purpose is to enrich the control mode of aerocraft, to lighten the pilot handling intensity, to improve manipulative speed and security. The paper has important practical significance and value to development of our country aviation project.
First, the paper analyzes the reasons that the detect performance of the traditional speech endpoint detection algorithm to apply in the aerial background dropped, studies the aerial noise in the intensity and type of noise, and gives a word boundary detection algorithm for variable noise environment The simulation result indicates that this performance of the endpoint decetion algorithm surpasses the traditional algorithm obviously under every kinds of noise environment. Moreover, the paper studies the traditional feature extract algorithm of MFCC in the computational complexity, finds that its computation is very big, which affects system real time. For the problem the paper improves the algorithm, ascertain the algorithmic optimum parameter by many experiment. The improved algorithm reduces the computation to half, corresponding recognition rate only cuts down 1.5%, which disregardes the effect to applying need.
The paper also introduces the hidden Markov model technology in speech recognition's application, studies the algorithmic basal principle and realization method of the acoustics model, language model and searching algorithm. For traditional Viterbi beam searching algorithm using fixed pruning threshold value's shortcoming, the paper uses the self-adjusting pruning threshold searching algorithm.
Finally, the paper constructs one small continuous speech command recognition system based on aerocraft with Visual C++, confirms the optimization parameter. This speech command recognition system's average recognition rate achieves 98.5%.

Key words: continuous speech recognition, speech command, endpoint detection, MFCC, aerial noise, search algorithm

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Post time 2008-1-11 23:06:15 |Display all floors

中文是这样的。我觉英文很蹩脚,但自己也改不出来。

摘    要
本课题主要研究在航空领域中飞行器语音指令识别技术。研究目的是丰富飞行器控制方式,减轻飞行员操作强度,提高控制速度和安全性能。本课题对我国航空事业的发展具有重要的现实意义和实用价值。
首先,论文分析了传统语音端点检测算法应用于航空背景检测性能下降的原因,从强度和类型两个方面对航空噪声进行了研究,给出了一个门限值自适应调整的基于变噪声环境语音端点检测算法。仿真结果表明,该算法在各种噪声环境下的端点检测性能明显优于传统算法。另外,从计算复杂度的角度对传统的美尔频率倒谱参数提取算法进行了分析研究,发现其计算量太大,影响系统实时性。针对这一问题对算法进行了改进,经多次实验确定了算法的最优参数。改进后的算法在计算量上减少了一半,相应的识别率仅减少1.5%,对应用需求的影响可忽略不计。
论文中还介绍了隐马尔可夫模型技术在语音识别中的应用,研究了声学模型、语言模型和搜索算法的基本原理和实现方法,针对传统Viterbi beam搜索算法设定固定剪枝门限值的缺点,采用可自适应调整剪枝门限的搜索算法。算法分析结果表明,该算法有一定的优越性。
最后,使用Visual C++开发平台构建了一个小型的基于飞行器的连续语音指令识别系统,设定了最优参数,该语音指令识别系统的平均识别率达到98.5%。



关键词:连续语音识别,语音指令,端点检测,美尔倒谱参数,航空噪声,搜索算法

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