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English vowel identification in long-term speech-shaped noise and multi-talker babble for English and Chinese listeners
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FIG. 1.

Average percent correct vowel (top) identification scores and standard errors and (bottom) native advantage over the 12 vowels as a function of listening conditions in (left) LTSSN and (right) MTB for three groups of listeners (EN, CNU, and CNC). Native advantage was computed by subtracting the identification scores of non-native listeners from the scores of native listeners.

Image of FIG. 2.

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FIG. 2.

The amount of masking release as a function of SNRs for EN, CNU, and CNC groups. The masking release was calculated as the difference between vowel identification scores in MTB and those in LTSSN at each SNR. A positive masking release means better performance in babble; a negative masking release means better performance in LTSSN.

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/content/asa/journal/jasa/133/5/10.1121/1.4800191
2013-04-10
2014-04-16

Abstract

The identification of 12 English vowels was measured in quiet and in long-term speech-shaped noise (LTSSN) and multi-talker babble for English-native (EN) listeners and Chinese-native listeners in the U.S. (CNU) and China (CNC). The signal-to-noise ratio was manipulated from −15 to 0 dB. As expected, EN listeners performed significantly better in quiet and noisy conditions than CNU and CNC listeners. Vowel identification in LTSSN was similar between CNU and CNC listeners; however, performance in babble was significantly better for CNU listeners than for CNC listeners, indicating that exposing non-native listeners to native English may reduce informational masking of multi-talker babble.

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Scitation: English vowel identification in long-term speech-shaped noise and multi-talker babble for English and Chinese listeners
http://aip.metastore.ingenta.com/content/asa/journal/jasa/133/5/10.1121/1.4800191
10.1121/1.4800191
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