The Rise of AI Voice Cloning: A New Threat in Cybersecurity

Context: Voice clone fraud has been on the rise in India as voice cloning through artificial intelligence is  increasingly being used for scams.

AI Voice Scams: Alarming Statistics from India

• The Artificial Imposter Report, 2022: It revealed that 47% of surveyed Indians have either been a victim or knew someone who had fallen prey to an AI-generated voice scam. 
  • For instance, recently a Lucknow resident fell prey to a cyberattack that used AI to impersonate the voice of the victim’s relative, requesting the person to transfer a substantial amount through UPI. 
• AI Voice Scams: According to McAfee, 66% of Indian participants admitted that they would respond to a voice call or a phone call that appeared to be from a friend or family member in urgent need of money. 

Must Read: NCRB Data On Cyber Crime In India

About Voice Cloning

• Voice Cloning: It is the process of creating a synthetic voice using the audio recordings of a real person. 

• AI Voice Cloning: Voice cloning using Artificial Intelligence (AI) techniques to train a Machine Learning voice model on real recordings can extract spectrums of the voice and create a voice that sounds almost exactly like the real voice.
  • For instance, voice cloning using advanced deep learning techniques can create expressive, emotional, and emotional voice clones that resemble 99% of the real voice.
• Misuse of Voice Clones: Scammers use an audio clip of an individual and upload their voice clip to an online program that is able to replicate the voice almost accurately. 
• Voice Cloning Services: There’s a host of these applications online with popular ones like Murf, Resemble, Speechify, etc.

Voice Cloning Working Mechanism

• Data Collection and Preprocessing: To clone voices effectively, an extensive dataset of voice samples is required. 
  • Once collected, these audio samples undergo preprocessing, where the sounds are cleaned, organized, and formatted to be fed into the AI models.
• Role of Neural Networks: These advanced AI frameworks scrutinize the raw audio data extract patterns and decipher the complex web of sound. 
• Generative Adversarial Networks (GANs): A dynamic framework propels the technology’s capability to clone voices. It comprises two components viz. the generator and the discriminator.
  • The generator’s role is to create synthetic voices.
  • The discriminator undertakes the task of differentiating between generated and authentic human voices. 
• Creating Authentic Voices: The process of AI voice cloning culminates in the creation of authentic voices. 

News Source: TH

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