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Voice Fingerprinting for Indoor Localization by leo ling is a document available to read on EtoBox.

This document presents a study on voice fingerprinting for indoor localization using a single microphone array and deep learning techniques. The proposed system utilizes a ReSpeaker 6-mic circular array connected to a Raspberry Pi, employing transfer learning and deep convolutional neural networks to achieve effective location estimation in complex indoor environments. Experimental results indicate that the Inception-ResNet-v2 model can provide satisfactory localization performance with minimal errors in tw

Author
leo ling
Language
EN