Network and Embedded Applications of Automatic Speech Recognition

ASR (Automatic Speech Recognition) is one of key technologies in the upcoming Ubiquitous Computing and Ambient Intelligence. In this paper, first, the surveys on processing devices such as microprocessors and memories, and on communication infrastructure, especially wireless communication infrastructure re-lating to ASR are reported. Second, the embed-ded version of CSR (Continuous Speech Recognition) software for the mobile environmental use of ASR is reported. As the devices, RISC based microprocessors, semi-conductor memories, and HDD are summarized. For the communication infrastructure, mobile communi-cations and wireless LANs are described. Finally, im-plementation results of the free CSR software called Julius on the T-engineTM consisting of an SH-4A mi-croprocessor are reported

Embedded Julius: Continuous Speech Recognition Software for Microprocessor

MMSP2006: IEEE 8th International Workshop on Multimedia Processing, October 3-6, 2006, Victoria, British Colombia, Canada.To expand CSR (continuous speech recognition) software to the mobile environmental use, we have developed embedded version of "Julius". Julius is open source CSR software, and has been used by many researchers and developers in Japan as a standard decoder on PCs. Julius works as a real time decoder on a PC. However further computational reduction is necessary to use Julius on a microprocessor. Further cost reduction is needed. For reducing cost of calculating pdfs (probability density function), Julius adopts a GMS (Gaussian mixture selection) method. In this paper, we modify the GMS method to realize a continuous speech recognizer on microprocessors. This approach does not change the structure of acoustic models in consistency with that used by conventional Julius, and enables developers to use acoustic models developed by popular modeling tools. On simulation, the proposed method has archived 20% reduction of computational costs compared to conventional GMS, 40% reduction compared to no GMS. Finally, the embedded version of Julius was tested on a developmental hardware platform named "T-engine". The proposed method showed 2.23 of RTF (real time factor) resulting 79% of that of no GMS without any degradation of recognition performance

Real-Time Continuous Speech Recognition System on SH-4A Microprocessor

MMSP2007: IEEE 9th International Workshop on Multimedia Signal Processing, October 1-3, 2007, Crete, Greece.To expand CSR (continuous speech recognition) software to the mobile environmental use, we have developed embedded version of Julius (embedded Julius). Julius is open source CSR software, and has been used by many researchers and developers in Japan as a standard decoder on PCs. In this paper, we describe an implementation of the embedded Julius on a SH-4A microprocessor. SH-4A is a high-end 32-bit MPU (720 MIPS) with on-chip FPU. However, further computational reduction is necessary for the embedded Julius to operate realtime. Applying some optimizations, the embedded Julius achieves real-time processing on the SH-4A. The experimental results show 0.89 times RT(real-time), resulting 4.0 times faster than baseline CSR. We also evaluated the embedded Julius on large vocabulary (20,000 words). It shows almost real-time processing (1.25 times RT)

Embedded JULIUS on T-Engine Platform

ISPACS2006: International Symposium on Intelligent Signal Processing and Communication Systems, December 12-15, 2006, Yonago, Japan.In this paper, we report implemental results of an embedded version of Julius. We used T-Enginetrade as a hardware platform which has a SuperH microprocessor. The Julius is free and open continuous speech recognition (CSR) software running on personal computers (PCs) which have huge CPU power and storage memory size. The technical problems to make Julius for embedded version are computing/process and memory reductions of Julius software. We realized 2.23 of RTF (real time factor) of embedded speech recognition processing on the condition of 5000-word vocabulary without any recognition accuracy degradation