【作者】 应俊；

【导师】 李刚；

【作者基本信息】 浙江工业大学 ， 通信与信息系统， 2010， 硕士

【摘要】 随着近年来信息技术尤其是计算机技术的高速发展,语音识别技术无论在理论还是在实践应用上都有了长足的进步和发展。其中部分较为成熟的技术已经在硬件上逐步得到实现,一些基于嵌入式或集成电路的小规模语音识别芯片也开始在人们的日常生活中有了初步的应用。然而,这些常见的语音芯片一般均采用DSP为核心的固定结构,不但费用高而且设计缺乏灵活性,难以进一步提高处理能力。本文在对孤立词语音识别的算法进行深入研究的基础上,针对传统算法的不足,在较为关键的语音端点检测和特征提取部分做了一些改进。在端点检测上,采用了具有抗干扰能力的零能积阈值判决法和状态机的设计方案;在特征提取上运用了更适合硬件设计的舒尔递推算法来求解自相关方程。这些改进不但提高了计算的效率,而且更有利于算法的硬件实现,从实验结果来看效果也比较理想。同时,针对当前语音芯片的不足,设计了基于SOPC的FPGA嵌入式系统对整个软件算法进行了实现。在硬件设计中,通过硬件DSP的Matlab建模设计等多种方法,使得传统Matlab算法与硬件的实际底层设计有机结合起来,并充分发挥了NiosⅡ软核处理器用户外设模块可订制、设计功能灵活的特点,对核心硬件系统的I2C主控配置模块、语音数据预处理模块、语音数据采集模块和语音识别软件算法模块分别进行了实现,取得了较好的效果。更多还原

【Abstract】 With the rapid development of information technology, especially in computer science, speech recognition has gained the great improvement both in theory and practice. Some of mature techniques have been realized by hardware or several speech recognition chips which are based on integrate circuit or embedded system. Due to the expensive price and the lack of design flexibility, the performance of these chips can’t be elevated currently.Based on thorough research on algorithms for isolated word recognition, this thesis makes improvements on the endpoint detection and feature extraction. We adopt zero-energy threshold judgment algorithm in detection. In the feature extraction, the Schur algorithm is used to solve the relevant equation, which is more appropriate for hardware implementation. All these not only increase the computation efficiency but also make the hardware implementation of the algrithms much easier, which has been supported by experiments.At the same time, we implement the whole algorithm of isolated word recognition on FPGA (Field Programmable Gate Array) embedded hardware system based on the concept of SOPC (System on a Programmable Chip). The abstract algorithm described in Matlab has been connected to the detailed hardware design by the tool of DSP Builder. The realization of the module of I2C configuration, module of speech data preprocessing, module of speech data collection and module of speech recognition have totally shown the advantage of NiosⅡsoft-core CPU in FPGA design, such as user-definable function.更多还原