5. The method for determining user liveness in accordance with claim 1 , said calculating a first matrix step comprising: determining at least one portion of the captured voice biometric data; calculating a spectral vector for the at least one portion; and concatenating the spectral vectors to create the first matrix.
1. A method for determining user liveness comprising: capturing, by a computing device, voice biometric data of a user during a verification transaction, the user and computing device being a user-computing device pair; calculating a first matrix for the captured voice biometric data; calculating an expansion coefficient matrix based on the first matrix and a record spectral shape matrix, the record spectral shape matrix being for the user-computing device pair; calculating a distortion vector as the average of a ratio between the first matrix and the product of the record spectral shape matrix and the expansion coefficient matrix; calculating a spectral property difference as an element-wise function between the square value of the distortion vector and the square value of a user record normalization vector; inputting the spectral property difference into a machine learning algorithm; calculating an output score with the machine learning algorithm, the output score representing the difference between a probability the voice biometric data was captured from a live user and a probability the voice biometric data was not captured from a live user; and determining the voice biometric data was captured from a live user when the output score satisfies a threshold score.