1. A method for speech recognition, comprising the steps of: generating a set of likely hypotheses using a speech recognition method for recognizing speech; rescoring the likely hypotheses by using sentence based semantic content and lexical content by employing a semantic structured language model which combines a semantic language model and a lexical language model wherein the semantic structured language model is trained by including a unigram feature, a bigram feature, a trigram feature, a current active parent label (Li), a number of tokens (Ni) to the left since current parent label (Li) starts, a previous closed constituent label (Oi), a number of tokens (Mi) to the left after the previous closed constituent label finishes, and a number of questions to classify parser tree entries, wherein the questions include a default, (wj−1), (wj−1, wj−2), (Li), (Li, Ni, wj−1), and (Oi, Mi), where w represents a word and j is and index representing word position; and scoring parse trees to identify a best sentence according to the sentences' parse tree by employing semantic information and lexical information in the parse tree to clarify the recognized speech.