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Temporal resolution analysis in frequency domain linear prediction
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Frequency domain linear prediction (FDLP) is a technique for auto-regressive modeling of Hilbert envelopes. In this letter, the resolution properties of the FDLP model are investigated using synthetic signals with impulses immersed in noise. The effect of various factors are studied which affect the temporal resolution and this analysis suggests ways to improve the resolution of the FDLP envelopes in noisy speech. The high resolution FDLP envelopes are used to derive robust features for phoneme recognition in noisy and reverberant speech. In these experiments, the FDLP features derived from high resolution envelopes provide significant improvements.
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