Efficient Adaptive Speech Reception Threshold Measurements Using Stochastic Approximation Algorithms.

This study examines whether speech-in-noise tests that use adaptive procedures to assess a speech reception threshold in noise (SRT50n) can be optimized using stochastic approximation (SA) methods, especially in cochlear-implant (CI) users. A simulation model was developed that simulates intelligibi...

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Publicado en:Trends in Hearing Vol. 24; pp. 1 - 18
Autores principales: Dingemanse, Gertjan, Goedegebure, André
Formato: equations & formulas research tables/charts Journal Article
Publicado: Sage Publications Inc. 5/19/2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 5/19/2020
      vid: 24
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      pub: Sage Publications Inc.
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        10.1177/2331216520919199
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        atl: Efficient Adaptive Speech Reception Threshold Measurements Using Stochastic Approximation Algorithms.
      aug:
        au:
          Dingemanse, Gertjan
          Goedegebure, André
        affil: Department of Otorhinolaryngology and Head and Neck Surgery, 6993 -->Erasmus Medical Center -->, Rotterdam, the Netherlands
      sug:
        subj:
          Speech Reception Threshold Test
          Cochlear Implant
          Auditory Perception
          Speech Intelligibility
          Listening
          Algorithms
          Human
          Noise
          Speech Perception
      ab: This study examines whether speech-in-noise tests that use adaptive procedures to assess a speech reception threshold in noise (SRT50n) can be optimized using stochastic approximation (SA) methods, especially in cochlear-implant (CI) users. A simulation model was developed that simulates intelligibility scores for words from sentences in noise for both CI users and normal-hearing (NH) listeners. The model was used in Monte Carlo simulations. Four different SA algorithms were optimized for use in both groups and compared with clinically used adaptive procedures. The simulation model proved to be valid, as its results agreed very well with existing experimental data. The four optimized SA algorithms all provided an efficient estimation of the SRT50n. They were equally accurate and produced smaller standard deviations (SDs) than the clinical procedures. In CI users, SRT50n estimates had a small bias and larger SDs than in NH listeners. At least 20 sentences per condition and an initial signal-to-noise ratio below the real SRT50n were required to ensure sufficient reliability. In CI users, bias and SD became unacceptably large for a maximum speech intelligibility score in quiet below 70%. In conclusion, SA algorithms with word scoring in adaptive speech-in-noise tests are applicable to various listeners, from CI users to NH listeners. In CI users, they lead to efficient estimation of the SRT50n as long as speech intelligibility in quiet is greater than 70%. SA procedures can be considered as a valid, more efficient, and alternative to clinical adaptive procedures currently used in CI users.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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