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Advances in human computer interaction (HCI) technology has resulted in widespread development of natural language and speech applications. These applications are known to be computationally different from other end-user applications. In this paper, the architectural features of text to speech (TTS) and automatic speech recognition (ASR) applications have been evaluated and cost effective optimal architectural solutions have been suggested. The results have shown that low cost solutions such as ISA extension and feature addition to an existing embedded architecture can lead to appreciable improvement in performance for these applications. This work also presents a design space exploration to suggest an optimized VLIW architecture for TTS and ASR applications.