A needs-driven cognitive architecture for future 'intelligent' communicative agents

Recent years have seen considerable progress in the deployment of 'intelligent' communicative agents such as Apple's Siri, Google Now, Microsoft's Cortana and Amazon's Alexa. Such speech-enabled assistants are distinguished from the previous generation of voice-based systems in that they claim to offer access to services and information via conversational interaction. In reality, interaction has limited depth and, after initial enthusiasm, users revert to more traditional interface technologies. This paper argues that the standard architecture for a contemporary communicative agent fails to capture the fundamental properties of human spoken language. So an alternative needs-driven cognitive architecture is proposed which models speech-based interaction as an emergent property of coupled hierarchical feedback control processes. The implications for future spoken language systems are discussed.