Informational masking and the effects of differences in fundamental frequency and fundamental-frequency contour on phonetic integration in a formant ensemble


Creators: Summers, Robert and Roberts, Brian
Keywords: Speech intelligibility; Formant integration; Informational masking; Competition; Speech segregation; Target-masker similarity
Divisions: College of Health and Life Sciences > Clinical and Systems Neuroscience
Funders: Economic and Social Research Council
Projects: Understanding speech in the presence of other speech: Perceptual mechanisms for auditory scene analysis in human listeners
Grant number: ES/K004905/1
Data Publisher: Aston University
Date Made Available: 20 October 2016
Collection period:
20 October 2016UNSPECIFIED
Data Collection and Processing Methods: These datasets comprise listeners’ transcriptions of sentence-length speech stimuli for Experiments 1 and 2 of the article of the same title (Summers, Bailey, and Roberts, 2016, Hearing Research). Each spreadsheet comprises two summary worksheets and the raw data for each listener. The summary worksheets contain aggregated scores (keywords correct by tight and loose scoring, see below) for each listener in each condition, with relevant demographic information. Subsequent worksheets comprise the raw data for each listener and stimulus. The raw data comprise: (a) the stimulus presented [Column heading: Text], (b) the listener’s response [Transcription], (c) the condition number for which the stimulus was presented [Condition] (note: condition number in article does not always correspond to that assigned when the experiment was run), (d) the number of times the listener heard the stimulus (up to 3 times in Experiment 1; once only in Experiment 2), (e) the number of keywords in the stimulus, (f) the loose score (number of keywords reported correctly for which the stem of the word is correct – e.g., “type”, “types”, and “typed” would all be marked correct for keyword “typing”), and (g) the tight score (only exactly reported keywords are marked as correct; homonyms are accepted). The mean scores (loose or tight) for each condition are computed by dividing the number of correct keywords reported for all 6 sentences in the condition by the total number of keywords.
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