Pole-focused linear prediction-based spectrogram for coarticulation analysis

Coarticulation refers to the influence of the articulation of one sound on the articulation of another sound in the same utterance. Effects of the coarticulation in an utterance have to be analyzed for developing a triphone-based speech recognition system, text-to-speech (TTS) system, etc. The conventional Fourier transform-based spectrogram fails to capture the formant transitions between two adjacent phonemes. Further, depending on the size of the analysis window, either horizontal or vertical striations are observed, which affects the clarity of the spectrogram. In this work, to overcome these problems, a linear prediction-based (a model-based) spectrogram is suggested and implemented. To further improve the clarity and to make the formant trajectories more prominent, the poles of the LP analysis are focussed and a modified LP-based spectrogram is derived. The resultant pole-focussed LP-based spectrogram is found to be a better candidate for analyzing the coarticulation effects. Using this technique, a matlab-based, user-friendly tool is developed for coarticulation analysis.