@article{
 title = {Automatic Estimation of Biosignals From the Human Voice},
 type = {article},
 year = {2015},
 keywords = {article,invited,journal},
 pages = {114:48--50},
 volume = {350},
 websites = {http://science.sciencemag.org/content/350/6256/114.3},
 month = {10},
 day = {2},
 id = {ae565926-b4c4-3ce0-85f7-b87d4b9cf026},
 created = {2024-08-09T12:19:59.499Z},
 file_attached = {true},
 profile_id = {ffa9027c-806a-3827-93a1-02c42eb146a1},
 group_id = {da2a8249-fdf4-3036-ba56-7358198a1600},
 last_modified = {2024-08-09T12:20:25.878Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {coutinho2015automaticvoice},
 source_type = {article},
 notes = {invited contribution},
 private_publication = {false},
 abstract = {Computational paralinguistics (CP) is a relatively new area of research that provides new methods, tools, and techniques to automatically recognize the states, traits, and qualities embedded in the nonsemantic aspects of human speech (1). In recent years, CP has reached a level of maturity that has permitted the development of a myriad of applications in everyday life, such as the automatic estimation of a speaker’s age, gender, height, emotional state, cognitive load, personality traits, likability, intelligibility, and medical condition (2). Here, we provide an overview of one particular application of CP that offers new solutions for health care—the recognition of physiological parameters (biosignals) from the voice alone.},
 bibtype = {article},
 author = {Coutinho, E and Schuller, Björn W.},
 journal = {Science},
 number = {6256}
}

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