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Okko Räsänen

Misc stuff (data, scripts etc.)

  • Sonority-envelope based algorithm for automatic syllabification of speech (from Räsänen, Doyle & Frank, Cognition, in press).

  • MATLAB toolbox for approximate variational inference of Dirichlet and Pitman-Yor process -based Bayesian mixture models with Gaussian or Von Mises-Fisher mixture components. Used in: Seshadri S., Remes U. & Räsänen O. "Dirichlet process mixture models for clustering i-vector data" (2017) and in "Comparison of Non-parametric Bayesian Mixture Models for Syllable Clustering and Zero-Resource Speech Processing" (2017).

  • Syllable-based algorithms for Zero Resource Speech Processing. Unsupervised word discovery codes for MATLAB from the paper by Räsänen, Doyle & Frank Proc. Interspeech-2015 as part of the Zero Resource Speech Processing Challenge .

  • Weakly supervised learning dataset (WSDL). WSDL is a compact dataset for testing and comparing weakly supervised pattern discovery algorithms.

  • Feature selection algorithms. MATLAB implementations of mutual information (MI), statistical dependency (SD), and random subset feature selection (RSFS) feature selection algorithms presented in Pohjalainen, Räsänen & Kadioglu (Comp. Speech and Language, 2015).


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