13. An apparatus for measuring the quality of speech communicated using packets, comprising: a plurality of N independent neural networks, each neural network being configured to process one of N separate sets of speech signal feature measurements corresponding to a speech signal recovered from packets communicated via a communications network to generate from the processed set of speech signal feature measurements a signal feature quality score, each of the N different neural networks corresponding to a different one of the N sets of speech signal feature measurements, said N neural networks generating N signal feature quality scores, each one of the N signal feature quality scores corresponding to a different one of N speech signal features; a joint quality score determination neural network configured to generate a joint signal feature quality score from said N signal feature quality scores; a score adjustment module configured to adjust said joint quality score based on packet loss information and codec type to generate a final overall quality score for said recovered speech signal wherein different types of codecs correspond to different packet loss robustness factors; and wherein said N sets of separate speech signal feature measurements include at least two sets of speech signal measurements from a group of sets of speech signal feature measurements including: a set of signal to noise ratio measurements, a set of spectral clarity measurements, a set of linear prediction skew measurements, a set of linear prediction kurtosis measurements and a set of pitch average measurements.
13. An apparatus for measuring the quality of speech communicated using packets, comprising: a plurality of N independent neural networks, each neural network being configured to process one of N separate sets of speech signal feature measurements corresponding to a speech signal recovered from packets communicated via a communications network to generate from the processed set of speech signal feature measurements a signal feature quality score, each of the N different neural networks corresponding to a different one of the N sets of speech signal feature measurements, said N neural networks generating N signal feature quality scores, each one of the N signal feature quality scores corresponding to a different one of N speech signal features; a joint quality score determination neural network configured to generate a joint signal feature quality score from said N signal feature quality scores; a score adjustment module configured to adjust said joint quality score based on packet loss information and codec type to generate a final overall quality score for said recovered speech signal wherein different types of codecs correspond to different packet loss robustness factors; and wherein said N sets of separate speech signal feature measurements include at least two sets of speech signal measurements from a group of sets of speech signal feature measurements including: a set of signal to noise ratio measurements, a set of spectral clarity measurements, a set of linear prediction skew measurements, a set of linear prediction kurtosis measurements and a set of pitch average measurements. 17. The apparatus of claim 13 , further comprising: an interface including a receiver configured to receive said packets communicated via the communications network; a processing module configure to process said packets to recover said speech signal; and a packet loss estimate generation module configured to generate, from the recovered speech signal, an estimate of the number of packets lost in the communication of said speech signal via said communications network.