19. A method of identifying phonemes within audible signal data, the method comprising: receiving, at one or more audio sensors, the audible signal data; synthesizing a plurality of features streams from the received audible signal data, the plurality of feature streams including a first feature stream and a plurality of targeted feature streams, wherein each of the plurality of targeted feature streams is associated with a respective problematic phoneme, wherein the first feature stream is generated primarily in order to provide audio information indicative of non-problematic phonemes, wherein each of the plurality of targeted feature streams is generated in order to provide audio information indicative of a corresponding problematic phoneme; generating a plurality of detection indicator values using a phoneme-specific experts system having a plurality of problematic phoneme-specific expert neural networks (PPENNs), wherein generation of the plurality of detection indicator values is correspondingly based on the plurality of targeted feature streams, and wherein each of the plurality of detection indicator values characterizes a respective probability that a corresponding problematic phoneme is present within the received audible signal data; assessing, using an ensemble phoneme recognition neural network, which of a plurality of phonemes is present within the received audible signal data based on a first feature stream and the plurality of detection indicator values; and synthesizing, by the ensemble phoneme recognition neural network, one or more phoneme candidates as recognized within the received audible signal data based on the first feature stream and the plurality of detection indicator values.
19. A method of identifying phonemes within audible signal data, the method comprising: receiving, at one or more audio sensors, the audible signal data; synthesizing a plurality of features streams from the received audible signal data, the plurality of feature streams including a first feature stream and a plurality of targeted feature streams, wherein each of the plurality of targeted feature streams is associated with a respective problematic phoneme, wherein the first feature stream is generated primarily in order to provide audio information indicative of non-problematic phonemes, wherein each of the plurality of targeted feature streams is generated in order to provide audio information indicative of a corresponding problematic phoneme; generating a plurality of detection indicator values using a phoneme-specific experts system having a plurality of problematic phoneme-specific expert neural networks (PPENNs), wherein generation of the plurality of detection indicator values is correspondingly based on the plurality of targeted feature streams, and wherein each of the plurality of detection indicator values characterizes a respective probability that a corresponding problematic phoneme is present within the received audible signal data; assessing, using an ensemble phoneme recognition neural network, which of a plurality of phonemes is present within the received audible signal data based on a first feature stream and the plurality of detection indicator values; and synthesizing, by the ensemble phoneme recognition neural network, one or more phoneme candidates as recognized within the received audible signal data based on the first feature stream and the plurality of detection indicator values. 22. The method of claim 19 , wherein synthesizing each of the plurality of feature streams includes generating a combination of spectral feature values including one or more of spectra values, cepstra values, mel-scaled cepstra coefficients, power normalized cepstral coefficients, a pitch value, a signal-to-noise ratio (SNR), a voice strength estimate, and a voice period variance estimate.