Article details

Research area
Natural language & AI

Automatic Speech Recognition on Mobile Devices and over Communication Networks



Energy aware speech recognition for mobile devices


As portable electronic devices move to smaller form-factors with more features, one challenge is managing and optimizing battery lifetime. Unfortunately, battery technology has not kept up with the rapid pace of semiconductor and wireless technology improvements over the years. In this chapter, we present a study of speech recognition with respect to energy consumption. Our analysis considers distributed speech recognition on hardware platforms with PDA-like functionality. We investigate quality of service and energy trade-offs in this context. We present software optimizations on a speech recognition front-end that can reduce the energy consumption by over 80% compared to the original implementation. A power on/off scheduling algorithm for the wireless interface is presented. This scheduling of the wireless interface can increase the battery lifetime by an order of magnitude. We study the effects of wireless networking and fading channel characteristics on distributed speech recognition using Bluetooth and IEEE 802.11b networks. When viewed as a whole, the optimized distributed speech recognition system can reduce the total energy consumption by over 95% compared to a software client-side ASR implementation. Error concealment techniques can be used to provide further energy savings in low channel SNR conditions.

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