ISSN : 1796-203X
Volume : 4    Issue : 2    Date : February 2009

Software/Hardware Co-design of HMM Based Speaker Independent Isolated Digit Recognition System
V. Amudha, B.Venkataramani, R. Vinoth kumar and S. Ravishankar
Page(s): 154-159
Full Text:
PDF (131 KB)

In this paper, the design and implementation results of a system on a chip (SOC) based speech
recognition system as software/hardware co-design is presented. The hidden markov model (HMM) is
used for the speech recognition. In order to implement this in SOC, the various tasks required are
optimally partitioned between hardware and software. The SOC, housed in Altera FPGA boards , has Nios
II soft core processor. Custom hardware blocks are developed for computationally intensive blocks such
as Viterbi decoder. The preprocessing and training of HMM are implemented in software (using C
program). The Viterbi decoding is implemented in hardware as custom block for real time recognition. It is
also implemented in software for verification and comparison. It is observed that the sequential hardware
implementation of viterbi block is 80 times faster than the software approach using C program with UP3
kit. An over all recognition accuracy of 94.8% is achieved for speaker independent digit recognition for our
own database of 6 speakers. Altera’s DE2 board with cyclone II FPGA is used to implement TI46 digit
recognition. Since the logical elements in DE2 board is high compared to UP3 kit the viterbi decoding is
implemented in parallel for 0-9 digits. Because of this speed of recognition is ‘772’ times faster than
software implementation with cyclone II FPGA. And also it is observed that for TI-46 speech database for f1
speaker the recognition accuracy is 87% using LPC as feature extraction technique. Extension of this work
for larger vocabulary size and using MFCC as feature extraction is under progress.

Index Terms
Software/hardware co-design, Custom hardware, SOC, HMM