1. A computer-implemented method of assessing non-native speech proficiency, comprising: processing, using a processing system, 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, using the processing system, the vowel sounds within the vowel sound boundaries to extract vowel characteristics; processing, using the processing system, 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 using the processing system, 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.
1. A computer-implemented method of assessing non-native speech proficiency, comprising: processing, using a processing system, 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, using the processing system, the vowel sounds within the vowel sound boundaries to extract vowel characteristics; processing, using the processing system, 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 using the processing system, 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. 7. The method of claim 1 , wherein one or more of the vowel space metrics are calculated based on a first vowel characteristic, formant F 1 , and a second vowel characteristic, formant F 2 ; wherein the vowel space metrics comprise an area of a vowel triangle defined by a mean F 1 and F 2 values of the AA, IY, and OW vowel sounds.