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

机译：基于模糊逻辑的文本无关Fongbe语音分割算法

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摘要

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.
机译：在本文中，我们提出了一种使用模糊逻辑方法从非线性语音分析中执行连续语音分割任务的算法。所提出的算法基于时域特征。这些特征是短期能量，过零率和在信号的每个点计算出的奇异指数。我们使用了有关通过检查特征时间演变而提供的细分的相关信息。对于音素或音节识别和过渡音而言，此功能关闭。模糊逻辑技术帮助我们将计算出的特征模糊化为三个互补集合，即低，中，高，并使用一组模糊规则执行匹配阶段。我们提出的算法的输出是静音，音素或音节。经过评估，我们的算法在使用贝宁，多哥和尼日利亚等非洲口音的情况下，产生了最佳效果，并获得了有效的结果。

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