基于fpga的离散阿拉伯语语音识别HMM

F. A. Elmisery, A. Khalil, A. Salama, H. F. Hammed
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引用次数: 24

摘要

在这项工作中,我们提出了一个基于硬件/软件协同设计实现方法的阿拉伯语语音识别系统。语音识别是一项计算量很大的任务,尤其是模式匹配阶段。隐马尔可夫模型被认为是各种语音识别任务中最强大的建模和匹配技术。使用专用硬件实现模式匹配算法,可以加快识别速度,而模式匹配算法耗时较长。本文利用现场可编程门阵列(FPGA)实现了一种基于HMM的模式匹配算法。对HMM匹配算法的核心——前向算法进行了分析和改进,使其更适合FPGA实现。实现结果表明,改进算法的识别精度与经典算法非常接近,并且在FPGA中实现了更高的速度和更少的占用面积。将该方法用于孤立的阿拉伯语单词识别,并取得了与强大的经典识别系统相当的识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A FPGA-based HMM for a discrete Arabic speech recognition system
In this work we propose a speech recognition system for Arabic speech based on a hardware/software co-design implementation approach. Speech recognition is a computationally demanding task, specially the pattern matching stage. The Hidden Markov Model (HMM) is considered the most powerful modeling and matching technique in the different speech recognition tasks. Implementing the pattern matching algorithm, which is time consuming, using dedicated hardware will speed up the recognition process. In this paper, a pattern matching algorithm based on HMM is implemented using Field Programmable Gate Array (FPGA). The forward algorithm, core of matching algorithm in HMM, is analyzed and modified to be more suitable for FPGA implementation. Implementation results showed that the recognition accuracy of the modified algorithm is very close to the classical algorithm with the gain of achieving higher speed and less occupied area in the FPGA. The proposed approach is used for isolated Arabic word recognition and achieved a recognition accuracy comparable with the powerful classical recognition system.
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