20. A computer-implemented system for assessing non-native speech proficiency, comprising: one or more data processors; and one or more memories, wherein the one or more data processors are configured to execute steps comprising: processing a non-native speech sample to identify vowel sounds in the non-native speech sample and vowel sound boundaries corresponding to the vowel sounds in the non-native speech sample; analyzing the vowel sounds within the vowel sound boundaries to extract vowel characteristics; processing the vowel sounds and the vowel characteristics to identify a plurality of vowel space metrics for the non-native speech sample, wherein the vowel space metrics indicate an extent of proficient utilization of AA, IY, and OW vowel sounds in the non-native speech sample; and generating a non-native speech proficiency score based upon the plurality of vowel space metrics for the non-native speech sample, wherein the non-native speech proficiency score provides a measure of a pronunciation proficiency of the non-native speech sample based upon the plurality of vowel space metrics, wherein the non-native speech proficiency score is generated by processing the plurality of vowel space metrics with a statistical computer model, the statistical computer model comprising multiple weighted features determined by training the statistical computer model relative to a plurality of training items, the training utilizing calculated vowel space metrics of the training items and human-scored non-native speech proficiency scores of the training items to determine values for the weighted features.
20. A computer-implemented system for assessing non-native speech proficiency, comprising: one or more data processors; and one or more memories, wherein the one or more data processors are configured to execute steps comprising: processing a non-native speech sample to identify vowel sounds in the non-native speech sample and vowel sound boundaries corresponding to the vowel sounds in the non-native speech sample; analyzing the vowel sounds within the vowel sound boundaries to extract vowel characteristics; processing the vowel sounds and the vowel characteristics to identify a plurality of vowel space metrics for the non-native speech sample, wherein the vowel space metrics indicate an extent of proficient utilization of AA, IY, and OW vowel sounds in the non-native speech sample; and generating a non-native speech proficiency score based upon the plurality of vowel space metrics for the non-native speech sample, wherein the non-native speech proficiency score provides a measure of a pronunciation proficiency of the non-native speech sample based upon the plurality of vowel space metrics, wherein the non-native speech proficiency score is generated by processing the plurality of vowel space metrics with a statistical computer model, the statistical computer model comprising multiple weighted features determined by training the statistical computer model relative to a plurality of training items, the training utilizing calculated vowel space metrics of the training items and human-scored non-native speech proficiency scores of the training items to determine values for the weighted features. 26. The computer-implemented system of claim 20 , wherein a forced alignment procedure is used to identify the plurality of vowel sound boundaries.