Advances in natural language processing.

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the linguistic structure of language and developing basic technologies such as machine translation, speech recognition, and speech synthesis. Today's researchers refine and make use of such tools in real-world applications, creating spoken dialogue systems and speech-to-speech translation engines, mining social media for information about health or finance, and identifying sentiment and emotion toward products and services.

Characterization of the biomedical query mediation process.

To most medical researchers, databases are obscure black boxes. Query analysts are often indispensable guides aiding researchers to perform mediated data queries. However, this approach does not scale up and is time-consuming and expensive.

Prosodic predictors of upcoming positive or negative content in spoken messages.

This article examines potential prosodic predictors of emotional speech in utterances perceived as conveying that good or bad news is about to be delivered. Speakers were asked to call an experimental confederate to inform her about whether or not she had been given a job she had applied for. A perception study was then performed in which initial fragments of the recorded utterances, not containing any explicit lexical cues to emotional content, were presented to listeners who had to rate whether good or bad news would follow the utterance.