The possibility to discriminate between speech and music signals by using a feature based on low frequency modulation has been investigated. Three different low frequency modulation parameters have been extracted and tested concerning the ability of discrimination. The low frequency modulation amplitudes calculated over 20 critical bands and their standard deviations were found to be good features for this discrimination task even with VQ models. They were also found to be less sensitive to channel quality and model size than MFCC features.