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Automated pitch-based gender recognition using an adaptive neuro-fuzzy inference system

机译:使用自适应神经模糊推理系统自动化基于俯仰的性别识别

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Results on classifying a speaker on the basis of gender by processing speech and analyzing the voice samples are presented. Firstly, the speech samples are classified into voiced/unvoiced/silence by using a speech classification algorithm implemented in MATLab. The pitch of the subject's voice is extracted from the classified speech sample. Following this, automated clustering is done by an Adaptive Neuro-Fuzzy Inference System (ANFIS) to separate male and female pitch values. An automated gender classification is successfully performed by ANFIS, although, the ANFIS has to be trained before the actual classification.
机译:结果通过处理言论对性别进行分类并分析语音样本进行分类。首先,通过使用在MATLAB中实现的语音分类算法,语音样本被分类为浊音/清洁/静音。从分类的语音样本中提取受试者声音的音高。在此之后,自动聚类由自适应神经模糊推理系统(ANFIS)完成,以分离雄性和凹音高值。 ANFIS成功执行自动性别分类,虽然,ANFIS必须在实际分类之前进行培训。

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