In this contribution we present a new approach for speech signal enhancement that improve a distorted speech signal in low SNR scenarios (at least if only a portion of the frequency range is highly disturbed). The approach consists of three algorithmic parts: a standard noise suppression unit, a partial speech reconstruction unit, and a time-frequency selective mixing unit. The basic idea of partial speech reconstruction is first to detect time-frequency areas where the SNR is still acceptable. These areas are used to extract relevant signal features such as the pitch frequency or the spectral envelope. Based on pre-trained signal models and the extracted features, the signal is reconstructed in a second stage. Finally, the reconstructed and the conventionally enhanced signals are mixed in a time-frequency selective manner. Subjective and objective tests indicate that a significant quality improvement is possible compared to conventional schemes - especially in high noise conditions.


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    Title :

    Model-based speech enhancement for automotive applications


    Contributors:
    Krini, M. (author) / Schmidt, G. (author)


    Publication date :

    2009


    Size :

    6 Seiten, 12 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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