Speaker Identification using Speech Recognition

05/29/2022
by   Syeda Rabia Arshad, et al.
0

The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on the human voice biometric features like pitch, amplitude, frequency etc. We proposed an unsupervised learning model where the model can learn speech representation with limited dataset. Librispeech dataset was used in this research and we were able to achieve word error rate of 1.8.

READ FULL TEXT

page 1

page 2

page 3

research
06/02/2023

Improved DeepFake Detection Using Whisper Features

With a recent influx of voice generation methods, the threat introduced ...
research
11/11/2021

Towards an Efficient Voice Identification Using Wav2Vec2.0 and HuBERT Based on the Quran Reciters Dataset

Current authentication and trusted systems depend on classical and biome...
research
10/24/2020

Stop Bugging Me! Evading Modern-Day Wiretapping Using Adversarial Perturbations

Mass surveillance systems for voice over IP (VoIP) conversations pose a ...
research
01/29/2015

Implementation of an Automatic Syllabic Division Algorithm from Speech Files in Portuguese Language

A new algorithm for voice automatic syllabic splitting in the Portuguese...
research
03/25/2022

WaveFuzz: A Clean-Label Poisoning Attack to Protect Your Voice

People are not always receptive to their voice data being collected and ...
research
06/22/2016

A segmental framework for fully-unsupervised large-vocabulary speech recognition

Zero-resource speech technology is a growing research area that aims to ...

Please sign up or login with your details

Forgot password? Click here to reset