Investigating the role of the Lombard reflex in non-audible murmur (NAM) recognition

In this paper, we report non-audible murmur (NAM) recognition results in noisy environments and investigate the effect of the Lombard reflex on non-audible murmur recognition. Non-Audible murmur is speech uttered very quietly and captured through body tissue by a special acoustic sensor (e.g., NAMmicrophone). A system based on non-audible murmur recognition can be applied in cases when privacy is preferable in human-machine communication. Moreover, due to direct body-transmission, the environmental noises do not affect the performance markedly. Previously, we reported non-audible murmur automatic recognition in a clean environment with very promising results. We also carried out experiments using clean models and simulated noisy data, showing that the performance did not change significantly. Using, however, real noisy test data, the performance decreased markedly. To investigate this problem, we studied the Lombard reflex and conducted non-audible murmur recognition experiments using Lombard data. Results show, that Lombard reflex affects non-audible murmur recognition.