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

页码：118 / 122

页数：5

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