Noise robust speaker-independent speech recognition with invariant-integration features using power-bias subtraction
Florian Müller, Alfred Mertins · 2011
This paper presents new results about the robustness of invariantintegration features (IIF) in noisy conditions. Furthermore, it is shown that a feature-enhancement method known as “powerbias subtraction ” for noisy conditions can be combined with the IIF approach to improve its performance in noisy environments while keeping the robustness of the IIFs to mismatching vocaltract length training-testing conditions. Results of experiments with training on clean speech only as well as experiments with matched-condition training are presented. Index Terms: speech recognition, speaker independency, noise robustness, invariant integration, power normalization