Spectral magnitude normalisation and cepstral coefficient transform for noisy-Lombard speech recognition

摘要

The authors propose a degradation model which represents the spectral changes of speech signals by the Lombard effect and noise contamination in noisy environments. According to this model, spectral magnitude normalisation and cepstral coefficient transforms are used to restore the cepstrum of clean speech from noisy-Lombard speech.