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Uncertainty Propagation

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Robust Speech Recognition of Uncertain or Missing Data

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Abstract

While it is often fairly straightforward to estimate the reliability of speech features in the time-frequency domain, this may not be true in other domains more amenable to speech recognition, such as for RASTA-PLP features or those obtained with the ETSI advanced front-end. In such cases, one useful approach is to estimate the uncertainties in the domain where noise reduction preprocessing is carried out, and to subsequently transform the uncertainties, along with the actual features, to the recognition domain. In order to develop suitable approaches, we will first give a short overview of relevant strategies for propagating probability distributions through nonlinearities. Secondly, for some feature domains suitable for robust recognition, we will show possible implementations and sensible approximations of uncertainty propagation and discuss the associated error margins and trade-offs.

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Authors and Affiliations

  1. Electronics and Medical Signal Processing Group, TU Berlin, 10587, Berlin, Germany

    Ramón Fernandez Astudillo & Dorothea Kolossa

Authors
  1. Ramón Fernandez Astudillo
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  2. Dorothea Kolossa
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Correspondence to Ramón Fernandez Astudillo .

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Editors and Affiliations

  1. Institute of Communication Acoustics, Ruhr-Universität Bochum, Universitätsstrasse 150, Bochum, 44801, Germany

    Dorothea Kolossa

  2. , Dept. of Communications Engineering, University of Paderborn, Warburger Strasse 100, Paderborn, 33098, Germany

    Reinhold Häb-Umbach

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Astudillo, R.F., Kolossa, D. (2011). Uncertainty Propagation. In: Kolossa, D., Häb-Umbach, R. (eds) Robust Speech Recognition of Uncertain or Missing Data. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21317-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-21317-5_3

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