10. A method for a multilingual text-to-speech (TTS) system, implemented at least in part by a computer, the method comprising: providing a hidden Markov model (HMM) for a sound in a first language; providing a HMM for a sound in a second language; determining line spectral pairs for the sound in the first language; determining line spectral pairs for the sound in the second language; calculating a Kullback-Leibler divergence (KLD) score based at least on the line spectral pairs for the sound in the first language and the sound in the second language, wherein the KLD score indicates similarity/dissimilarity between the sound in the first language and the sound in the second language based on line spectral pairs that are independent of at least a line spectral pair located in an upper half of a frequency range used for measuring a Kullback-Leibler divergence; and building a multilingual HMM-based TTS system wherein the TTS system comprises shared sounds based on KLD scores.
14. The method of claim 10 wherein the sound in the first language comprises a context-dependent sound.