IIFCopy - a C++-implementation for the computation, extraction, and selection of Invariant Integration Features

    IIF Copy Screenshot

    Invariant integration features (IIFs) have been proposed as an alternative to the standard feature extraction methods for automatic speech recognition.

    The IIFs are based on the idea of constructing invariant features by integrating nonlinearly transformed input signals over a finite transformation group. In the context of feature extraction for ASR, monomials up to a certain order are a good choice as nonlinear functions. Experiments showed that the IIFs perform superior compared to MFCCs and PLPs, especially in mismatching training-testing conditions.

    IIFCopy is a completely new (w.r.t the previously published C-version) written implementation for the computation, selection, and reduction of IIFs. The download provides binaries for different architectures and platforms together with IIF sets and reduction data as well as a documentation in the file README.txt.



    • Müller, F. and Mertins, A.: Contextual invariant-integration features for improved speaker-independent speech recognition. Speech Communication, vol. 53, no. 6, pp. 830 - 841, 2011
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    • Müller, F. and Mertins, A.: Invariant Integration Features Combined with Speaker-Adaptation Methods. Proc. Int. Conf. Spoken Language Processing (Interspeech 2010-ICSLP), Makuhari, Japan, pp. 2622--2625, Sept. 2010
      BibTeX PDF


    • Müller, F. and Mertins, A.: Invariant-integration method for robust feature extraction in speaker-independent speech recognition. Proc. Interspeech 2009, Brighton, Sept. 2009
      BibTeX PDF