Dataset of a subject and modeling data for an auditory word identification task.
Data from the four experiments and model estimates
Method of presentation in the experiment: loudspeaker, headphones 3. Trial: Trial number in the experimental list
anonymized subject identifier
word identifier -german umlaute and special character coded as 'ae' 'oe' 'ue' and 'ss'
log of L1-norm
recognition decision (yes/no)
latency for recognition decision
log recognition RT
dictation accuracy (TRUE: correct word reported, FALSE otherwise) 15. DictationRT: response latency to typing onset
Denis Arnold, Fabian Tomaschek, Konstantin Sering, Florence Lopez, and R. Harald Baayen (2017). Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit PLoS ONE 12(4):e0174623. https://doi.org/10.1371/journal.pone.0174623
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