CASIA OpenIR  > 毕业生  > 硕士学位论文
嵌入式语音识别系统中拒识算法的研究及实现
Alternative TitleThe Research And Realization of Rejection Algorithm in Embedded Speech Recognition Systems
方敏
Subtype工学硕士
Thesis Advisor台宪青 ; 李成荣
2004-06-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword语音识别 统计 拒识 嵌入式系统 Speech Recognition Stochastic Methods Rejection Embedded Systems
Abstract语音识别技术经过多年发展正日趋成熟,各种语音识别系统也不断被 开发出来。走向产品化是语音识别技术的终极目标,为此需要解决抗噪声、 环境适应性、集外词检测与拒识等关键问题,以增强系统的鲁棒性和可靠 性。其中,由于现在大多数识别器存在词表限制,高效拒识功能的加入对 提高系统性能尤为重要。 本文首先回顾了拒识算法研究所依据的统计语音识别理论与方法,并 给出两种主流的汉语孤立词语音识别器:进而对语音识别拒识问题的本质 及各种解决方法进行深入剖析,包括主流的显式建模方法和隐式建模(即 可信度度量)方法:由于拒识算法目前大多受识别平台限制、与任务高度 相关,因此本文针对两种不同的孤立词识别器,分别研究对应的平台相关 拒识算法。在上述研究的基础上,本文进行平台无关拒识算法方面的一些 探索,提出基于音节段模型识别的拒识方法。 语音识别技术在嵌入式平台的应用是语音识别实用化、产品化的主要 方向。嵌入式语音识别系统(ESRS)的研究开发涉及软件和硬件、资源和性 能等多方面的协调,还涉及嵌入式环境下的特定算法,因而是一项富有挑 战性的课题。本文对此进行系统分析和研究,并结合具体实例详细阐述嵌 入式语音识别系统的设计原则、软硬件开发相关问题等。最后,对嵌入式 语音识别系统的未来工作进行了展望。
Other AbstractAfter many years' development, Automatic Speech Recognition (ASR) technology has been mature; and many ASR systems have been developed. However, there are still many challenges confronting researchers, such as noise reducing, environment adaptation and Out-Of-Vocabulary (OOV) words detection and rejection etc. It is important to solve these problems to enhance the robustness and reliability of ASR systems. In this paper we briefly look back on stochastic speech recognition fundamentals and the framework of ASR systems. Then we focus on the rejection problem in ASR. Our discussion of rejection problem ranges from its definition, essence and evaluation to the popular solutions nowadays. We note that researchers Usually solve it in two ways, namely explicit modeling and implicit modeling (mainly by confidence measure). Due to the constraints of specific ASR tasks and specific recognizer to rejection, we propose several platform-dependent rejection approaches in two ASR platforms which models whole word and mandarin tri-phone respectively. In addition, we try some platform-independent rejection algorithms based on Syllable Segmental Models (SSM). The application of ASR technology in embedded systems is an important direction for its popularization. The development of Embedded Speech Recognition Systems (ESRS) involves in many factors such as hardware and software, resources and performances etc. In this paper, we analyze and expound the main problems of ESRS in details and give several examples we made during postgraduate stage. Finally we discuss the promising prospect of ASR SOC.
shelfnumXWLW762
Other Identifier762
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6770
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
方敏. 嵌入式语音识别系统中拒识算法的研究及实现[D]. 中国科学院自动化研究所. 中国科学院研究生院,2004.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[方敏]'s Articles
Baidu academic
Similar articles in Baidu academic
[方敏]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[方敏]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.