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This paper uses a crowd-sourced definition of a speech phenomenon we have called "focus". Given sentences, text and speech, in isolation and in context, we asked annotators to identify what we term the "focus" word. We present their consistency in identifying the focused word, when presented with text or speech stimuli. We then build models to show how well we predict that focus word from lexical (and higher) level features. Also, using spectral and prosodic information, we show the differences in these focus words when spoken with and without context. Finally, we show how we can improve speech synthesis of these utterances given focus information.