Abstract
A prosody analyzer enhances the interpretation of natural language utterances. The analyzer is distributed over a client/server architecture, so that the scope of emotion recognition processing tasks can be allocated on a dynamic basis based on processing resources, channel conditions, client loads etc. The partially processed prosodic data can be sent separately or combined with other speech data from the client device and streamed to a server for a real-time response. Training of the prosody analyzer with real world expected responses improves emotion modeling and the real-time identification of potential features such as emphasis, intent, attitude and semantic meaning in the speaker's utterances.
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