Research on Phoneme Sequences for Language Identification and Concurrent Voice Transmission

Language Identification is process of identifying the language being spoken from a sample of speech by an unknown speaker. Most of the previous work in this field is based on the fact that phoneme sequences have different occurrence probabilities in different languages, and all the systems designed till now have tried to exploit this fact. Language identification process in turn consists of two sub-systems. First system converts speech into some intermediate form called as phoneme sequences, which are used to model the language by doing their probabilistic analysis in the second sub-system. In this project both of the sub-systems are targeted. First some algorithms are discussed for designing language models. Then an attempt is made to design an algorithm for extracting phoneme sequences in form of more abstract classes derived by statistical tools like Gaussian Mixture Models (GMM) and Hidden Markov Model (HMM).