1. A method, comprising the steps of: determining a vicinity from which speech input to a speech recognition system originates, wherein determining the vicinity comprises estimating a sound direction of a source of the speech input based on a signal processing method; obtaining non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein obtaining the non-acoustic data comprises capturing visual data of the vicinity of the speech input; identifying a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein identifying the subject speaker comprises: segmenting one or more faces from the captured visual data; detecting mouth motion on the one or more faces, wherein detecting the mouth motion comprises applying temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and selecting a face corresponding to the subject speaker from the one or more faces in response to determining that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extracting one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyzing the one or more extracted non-acoustic attributes, and assigning at least one demographic to the subject speaker based on the analysis; selecting at least one model for use by the speech recognition system based on the at least one demographic assigned to the subject speaker; adjusting the speech recognition system using the at least one selected model; and processing the speech input using the adjusted speech recognition system; wherein the steps are performed by at least one processor device coupled to a memory.
1. A method, comprising the steps of: determining a vicinity from which speech input to a speech recognition system originates, wherein determining the vicinity comprises estimating a sound direction of a source of the speech input based on a signal processing method; obtaining non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein obtaining the non-acoustic data comprises capturing visual data of the vicinity of the speech input; identifying a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein identifying the subject speaker comprises: segmenting one or more faces from the captured visual data; detecting mouth motion on the one or more faces, wherein detecting the mouth motion comprises applying temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and selecting a face corresponding to the subject speaker from the one or more faces in response to determining that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extracting one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyzing the one or more extracted non-acoustic attributes, and assigning at least one demographic to the subject speaker based on the analysis; selecting at least one model for use by the speech recognition system based on the at least one demographic assigned to the subject speaker; adjusting the speech recognition system using the at least one selected model; and processing the speech input using the adjusted speech recognition system; wherein the steps are performed by at least one processor device coupled to a memory. 20. The method of claim 1 , wherein detecting the mouth motion comprises applying the temporal differencing on a lower third of each of the one or more faces.