Voice Based Age, Accent and Gender Recognition

Nithin Kumar B; Manoj K R; Nagendra N S; Deepa Angadi

Voice Based Age, Accent and Gender Recognition

Authors: Nithin Kumar B, Manoj K R, Nagendra N S, Deepa Angadi

Unique Paper ID: 152296
Volume: 8
Issue: 2
PageNo: 841-845

Keywords: Random Forest K Nearest Neighbors XGBoost MFCC features.

Abstract:
Gender, Age and Accent recognition that is solely achieved by human speech which is an interesting subject in the field of Automatic Speech Recognition systems. In this project, we have introduced a way of classifying a humanâ€™s speech into different classes of Gender, Age and Accent. The classification used in this project is mainly based on Machine Learning Models. The Models are systematically trained on the audio data that is obtained from Mozilla Common Voice. The dataset only contained the audio files with the respective labels associated with it. The noisy data from the dataset have been filtered out before it is fed into the Machine Learning models. In our project, we are using Mel Frequency Cepstral Coefficients (MFCC). We are extending Accent classification into American, European and Indian. But, in our project â€œVoice based Age, Accent and Gender Recognitionâ€ we have extended our work to the classification of speech into Gender, Age and Accent.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 2
PageNo: 841-845

Voice Based Age, Accent and Gender Recognition

Available:https://ijirt.org/Article?manuscript=152296

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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