1. A computer-implemented method of scoring non-native speech, comprising: receiving a speech sample spoken by a non-native speaker; performing automatic speech recognition on the speech sample to generate a transcript of the speech sample; processing the speech sample to generate a plurality of speech metrics associated with the speech sample; applying a plurality of non-scorable response filters to the plurality of speech metrics; determining whether the speech sample is scorable or non-scorable based upon the transcript and a collective application of said non-scorable response filters, wherein said determining is based on assessment of audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, and whether the speech sample includes speech from an incorrect language; associating an indication of non-scorability with the speech sample when the sample is determined to be non-scorable; and providing the sample to a scoring model for scoring when the sample is determined to be scorable.
4. The method of claim 1 , wherein the non-scorable response filters are arranged in a particular order, and wherein the speech sample is determined to be scorable or non-scorable based on a serial filtering process.