A proposed speaker recognition method based on long-term voice features and fuzzy logic

Abstract EN

Speaker recognition depends on specific predefined steps.

The mostimportant steps are feature extraction and features matching.

In addition, the category of the speaker voice features has an impact on the recognitionprocess.

The proposed speaker recognition makes use of biometric (voice)attributes to recognize the identity of the speaker.

The long-term featureswere used such that maximum frequency, pitch and zero crossing rate(ZCR).

In features matching step, the fuzzy inner product was usedbetween feature vectors to compute the matching value between a claimedspeaker voice utterance and test voice utterances.

The experimentsimplemented using (ELSDSR) data set.

These experiments showed that therecognition accuracy is 100% when using text dependent Speaker recognition depends on specific predefined steps.

The mostimportant steps are feature extraction and features matching.

In addition, the category of the speaker voice features has an impact on the recognitionprocess.

The proposed speaker recognition makes use of biometric (voice)attributes to recognize the identity of the speaker.

The long-term featureswere used such that maximum frequency, pitch and zero crossing rate(ZCR).

In features matching step, the fuzzy inner product was usedbetween feature vectors to compute the matching value between a claimedspeaker voice utterance and test voice utterances.

The experimentsimplemented using (ELSDSR) data set.

These experiments showed that therecognition accuracy is 100% when using text dependent speakerrecognition