1. A computer-implemented method of scoring a speech sample, comprising: performing automatic speech recognition with an automatic speech recognizer to generate a transcription of the sample, the automatic speech recognizer comprising a computerized language model and a computerized acoustic model trained based on speech samples from multiple speakers, and storing words of the transcription in a first data structure; associating the words of the transcription with part of speech labels with a computer processing system based on an analysis of the words with the processing system; generating part of speech sequences based on the part of speech labels with the computer processing system and storing the part of speech sequences in a second data structure; generating a first vector comprising the part of speech sequences and associated first numerical weights, each first numerical weight indicating a relative frequency of the associated part of speech sequence in the speech sample or a presence of the associated part of speech sequence in the speech sample; calculating a similarity score between the first vector and each of multiple score-level vectors, each score-level vector comprising (i) part of speech sequences occurring in a set of speech samples of a training corpus, each speech sample of the set being assigned a same score, and (ii) associated second numerical weights, each second numerical weight being based on a relative frequency of the associated part of speech sequence in the set and a relative importance of the associated part of speech sequence in differentiating speech samples assigned the score of the set from speech samples assigned different scores; and comparing the similarity scores using the computer processing system and scoring the speech sample with a computerized scoring model based on the comparison.