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The common limitations in auditory temporal processing for Mandarin Chinese and Japanese.

Hikaru Eguchi1, Kazuo Ueda2, Gerard B Remijn3

  • 1Human Science Course, Graduate School of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan.

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Temporal degradation significantly impacts speech intelligibility in both tonal (Mandarin Chinese) and non-tonal (Japanese) languages. Intelligibility remains high for short speech segments but declines sharply as segments lengthen, suggesting a universal temporal processing mechanism.

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Area of Science:

  • Auditory Neuroscience
  • Speech Processing
  • Psychoacoustics

Background:

  • Temporal processing is crucial for speech intelligibility.
  • Understanding how temporal degradation affects different language types is important.

Purpose of the Study:

  • To investigate the effect of temporal degradation on speech intelligibility in Mandarin Chinese (tonal) and Japanese (non-tonal).
  • To explore the underlying temporal processing mechanisms in speech perception.

Main Methods:

  • Systematic temporal degradation of speech using mosaicking (averaging power in time-frequency units and removing temporal fine structure).
  • Assessing intelligibility across varying segment durations for both languages.
  • Employing local time-reversal as a secondary degradation method.

Main Results:

  • Intelligibility showed similar patterns for both tonal and non-tonal languages.
  • A performance ceiling was maintained up to ~40 ms segment duration.
  • Intelligibility gradually declined beyond 40 ms, reaching a floor around 150 ms or longer.
  • Similar limitations were observed with local time-reversal, suggesting a common temporal processing mechanism.

Conclusions:

  • Temporal degradation critically affects speech cues beyond tonal information.
  • Speech intelligibility is constrained by temporal processing limitations, consistent with a dual time-window model (~20-30 ms and ~200 ms).
  • A common temporal processing mechanism underlies speech perception across different language types.