3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker.
3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker. 5. The method of claim 3 further comprising: computing a set of projected first order statistics corresponding to the set of speech utterances, based on the i-vectors and the diagonalized approximations of the equivalent precision matrices computed; computing a diagonalized approximation of a cumulative equivalent precision matrix for the set of speech utterances based on the diagonalized approximations of precision matrices computed for each i-vector; and diagonalizing a transformation of the diagonalized approximation of the cumulative equivalent precision matrix computed; and wherein, computing the score includes computing the score based on the set of projected first order statistics, the diagonalized approximation of the cumulative equivalent precision matrix, and the diagonalized transformation of the diagonalized approximation of the cumulative equivalent precision matrix.