This paper proposes using modulation cepstrum coefficients instead of cepstral coefficients for extracting metadata information such as age and gender. These coefficients are extracted by applying discrete cosine transform to a time-sequence of cepstral coefficients. Lower order coefficients of this transformation represent smooth cepstral trajectories over time. Results presented in this paper show that cepstral trajectories corresponding to lower (3-14 Hz) modulation frequencies provide best discrimination. The proposed system achieves 50.2% overall accuracy for this 7-class task while accuracy of human labelers on a subset of evaluation material used in this work is 54.7%.
['Jitendra Ajmera', 'Felix Burkhardt']
Age and Gender Classification using Modulation Cepstrum