Vocal Tract Length Normalization using a Gaussian Mixture Model Framework for Query-by-Example Spoken Term Detection

Abstract

In this work, we explored hierarchical MoS2�nanomaterials�for soil moisture sensing (SMS) and tested their efficacy considering the operational aspects of the sensor. Carnation and marigold flower-like MoS2�nanostructures were prepared via facile hydrothermal processes with varying synthesis temperatures. The synthesized MoS2�nanostructures were well characterized by�XRD, FTIR, FESEM, EDS, and HRTEM and it is evident that the variation in the hydrothermal temperatures has a significant impact on the crystallinity, morphology, stoichiometry, dimensions, and lattice spacing. We found that hierarchical MoS2�marigold flower-like nanostructures offer the highest sensitivity of about 2000 %, when gravimetric water content (GWC) is varied from 1 % to 20 % GWC, which is one of the highest reported SMS. The sensors exhibit hysteresis of about ��4 % and response times of about 500�s. They were highly selective to moisture compared to the other salts like Na, K, Cd, and Cu present in the soil. The sensors were also unaffected by changing temperatures with a small 2�4 % between 20 �C and 65 �C.