An Algorithm Based on Fuzzy Logic for Text-Independent Fongbe Speech Segmentation

In this paper, we present an algorithm using fuzzy logic approach to perform the continuous speech segmentation task from non-linear speech analysis. The proposed algorithm is based on time domain features. These features are the short-term energy, zero crossing rate and the singularity exponents calculated in each point of signal. We used the relevant information regarding the segments provided by examining of the feature time evolution. This is down for the phonemes or syllables identification and the transition fronts. Fuzzy logic technique helped us to fuzzify the calculated features into three complementary sets namely: low, medium, high and to perform a matching phase using a set of fuzzy rules. The outputs of our proposed algorithm are silence, phonemes or syllables. Once evaluated, our algorithm produced the best performances with efficient results on an African tonal language spoken especially in Benin, Togo and Nigeria.