1. A speech recognition apparatus, comprising: an extractor configured to extract acoustic model-state level information corresponding to an input speech signal from a training data model set using at least one of a first feature vector based on a gammatone filterbank signal analysis algorithm and a second feature vector based on a bottleneck algorithm; and a speech recognizer configured to provide a result of recognizing the input speech signal based on the extracted acoustic model-state level information, wherein the extractor is configured to obtain the acoustic model-state level information by applying at least one of the first feature vector and the second feature vector to a Gaussian mixture model-hidden Markov model (GMM-HMM) technology based training data model set, and wherein the first feature vector is determined based on an intra-frame feature value associated with a feature of a rapid change in a spectrum of the input speech signal, a static feature value associated with a static feature of the input speech signal, and an inter-frame feature value associated with a dynamic feature of the input speech signal based on a lapse of a period of time.