27. A non-transitory computer-readable memory comprising computer-readable instructions, which when executed cause a processor to perform steps comprising: performing speech recognition on digitized speech using a non-native acoustic model trained with non-native speech to generate word hypotheses for the digitized speech; performing time alignment between the digitized speech and the word hypotheses utilizing a reference acoustic model trained with native-quality speech; calculating statistics regarding individual words and phonemes of the word hypotheses based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics; calculating an assessment score based on one or more of the calculated features; and storing the assessment score in a computer-readable memory.
27. A non-transitory computer-readable memory comprising computer-readable instructions, which when executed cause a processor to perform steps comprising: performing speech recognition on digitized speech using a non-native acoustic model trained with non-native speech to generate word hypotheses for the digitized speech; performing time alignment between the digitized speech and the word hypotheses utilizing a reference acoustic model trained with native-quality speech; calculating statistics regarding individual words and phonemes of the word hypotheses based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics; calculating an assessment score based on one or more of the calculated features; and storing the assessment score in a computer-readable memory. 39. The non-transitory computer-readable memory of claim 27 , wherein the assessment score is based on one or more features selected from the group consisting of: an average likelihood across all letters: L 1 /m, where L 1 is a summation of likelihoods of all individual words: L 1 = ∑ i = 1 n ⁢ L ⁡ ( x i ) , where L(x i ) is a likelihood of word x i being spoken given an observed audio signal, where n is a number of words in a response, where m is a number of letters in the response; an average likelihood across all words: L 1 /n; an average likelihood per second normalized by a rate of speech: L 4 /R, where L 4 =L 1 /T, where T is the summation of a duration of all words in the response, where R=m/T s , where T s is a duration of the response; an average likelihood density across all words normalized by a rate of speech, L 5 /R, where L 5 = ∑ i = 1 n ⁢ L ⁡ ( x i ) t i n , where t i is a duration of word i in a response; an average vowel duration shift: S _ = ∑ i = 1 N v ⁢ S v i N v , where N v is a total number of vowels, where S v i is the duration shift of vowel v i , which is measured as an absolute value of the difference between a duration of vowel v i and a standard value of a duration of a vowel estimated on native speech data, where S v i =|P v i −D v i |, where P v i is the duration of vowel v i and D v i is the standard average duration of vowel v i ; and an average normalized vowel duration shifts: S _ ⁢ n = ∑ i = 1 N v ⁢ Sn v i N v , where Sn v i is a normalized duration shift of vowel v i , which is measured as an absolute value of a normalized difference between a duration of vowel v i and a standard value of a duration of a vowel estimated on the native speech data, where Sn v i is calculated as  P v i P - D v i D  , where P v i is the duration of vowel v i , P is an average vowel duration across all vowels in the response being scored, D v i is a standard average duration of vowel v i , and D is a standard vowel duration estimated on all vowels in native speech data.