An estimated-SN(Signal Noise)-ratio is calculated for a time-series feature vector of noise-superimposed speech by using a noise-free speech model and a noise model. A noise-superimposed model is generated based on the estimated-SN-ratio. A likelihood between the time-series feature vector of noise-superimposed speech and the noise-superimposed model is calculated to obtain likelihood information. A noise spectrum included in the noise-superimposed speech is estimated from the likelihood information.
Speech recognition apparatus and method in noisy circumstances