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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Invariant Features and Enhanced Speaker Normalization for Automatic Speech Recognition

Invariant Features and Enhanced Speaker Normalization for Automatic Speech Recognition

Muller, Florian

Paperback

Technology & Engineering

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ISBN10: 3832533192
ISBN13: 9783832533199
Publisher: Logos Verlag Berlin
Published: Jan 31 2013
Pages: 247
Weight: 0.65
Height: 0.56 Width: 5.68 Depth: 8.04
Language: English
Automatic speech recognition systems have to handle various kinds of variabilities sufficiently well in order to achieve high recognition rates in practice. One of the variabilities that has a major impact on the performance is the vocal tract length of the speakers. Normalization of the features and adaptation of the acoustic models are commonly used methods in speech recognition systems. In contrast to that, a third approach follows the idea of extracting features with transforms that are invariant to vocal tract lengths changes. This work presents several approaches for extracting invariant features for automatic speech recognition systems. The robustness of these features under various training-test conditions is evaluated and it is described how the robustness of the features to noise can be increased. Furthermore, it is shown how the spectral effects due to different vocal tract lengths can be estimated with a registration method and how this can be used for speaker normalization.

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