Speech and phoneme segmentation under noisy environment through spectrogram image analysis

This paper presents a new algorithm for speech segmentation based on image analysis of the spectrogram of the signal. The algorithm works in two loops: the first segments the sound in search for the speech signal. The segmented speech returns to the algorithm for phoneme segmentation. For evaluation, the algorithm was applied to TIMIT speech signals with correct speech segmentation of every tested signal, including signals under real-world noise.