The document discusses Muhammad Adil Raja's research project on non-intrusive real-time quality assessment of speech for VoIP using Hidden Markov Models. It describes using HMMs with a mixture density function and a few Gaussians to calculate the probability of an observation sequence and find the most likely state sequence that could have emitted it, based on the Viterbi algorithm and dynamic programming. It asks for recommendations on applications that can access the Viterbi probability, mentioning HTK, HMM Toolbox by Kevin Murphy, and Sphinx4 as options already considered.