Speech Recognition System for Embedded Real-time Applications

被引：7
|
作者：
Cheng, Octavian [1 ]
Abdulla, Waleed [1 ]
Salcic, Zoran [1 ]
机构：
[1] Univ Auckland, Dept Elect & Comp Engn, Auckland 1, New Zealand
来源：
2009 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT 2009) | 2009年
关键词：
Speech recognition; Embedded application; Real-time system; Softcore processor; Field Programmable Gate Arrays;
D O I：
10.1109/ISSPIT.2009.5407487
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper a hardware/software co-processing speech recognizer for embedded applications is proposed. The system mainly consists of a softcore processor and a hardware accelerator The accelerator is responsible for GMM emission probability calculation, which is the major computational bottleneck. To alleviate the memory bandwidth issue, the hardware accelerator uses double-buffering, which allows parallel operation of data retrieval and GMM computation. The proposed accelerator is synthesized on an Altera Stratix II FPGA device together with a Nios II softcore processor running at 100MHz. The proposed system is compared with a pure software-based system using test utterances from the Resource Management (RM1) corpus. For a speech utterance length of 2.49s, the decoding time reduces from 6.64s to 2.48s. The real-time factor improves from 2.67 to 1.00. The word accuracy rate of the proposed system on the RM corpus is 93.42%.
引用
收藏
页码：118 / 122
页数：5
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