Deepfakes have become increasingly sophisticated and easier to create over the years. Today, hackers can manipulate a person’s voice using just seconds of audio, allowing them to steal the identity of not only customers but also employees and executives.

The consequences of voice cloning reach far beyond individual identity theft — it can pose a severe threat to financial institutions and even destabilize the stock market. Recent incidents, such as the reported deepfake voice heist in Japan where a fraudster cloned a company director’s voice to steal $35 million, highlight the urgent need for solutions.

This issue is not confined to a specific region; it’s a growing epidemic in America. According to Federal Trade Commision data, consumers lost almost $9 billion to fraud last year. The global impact is projected to skyrocket to $10.5 trillion by 2025.

Recognizing the severity of the situation, on November 16, the FTC announced an exploratory Voice Cloning Challenge. The goal is to stimulate the development of multidisciplinary solutions that protect consumers from the malicious use of AI technologies, specifically in voice cloning.

In other words: the FTC wants technologists and members of the public to come up with ways to stop voice clones from tricking people.

What is Voice Cloning?

Voice cloning is a sophisticated technology that involves creating a synthetic reproduction of an individual’s voice using advanced AI algorithms. The process typically begins with the collection of audio data featuring the target’s voice. A few years ago, one would need hours of someone’s voice but now, all it takes in a few seconds of audio.

This dataset serves as the basis for training the AI model, enabling it to analyze and understand the nuances, intonations, and unique characteristics of the person’s speech patterns.

Once the AI model is sufficiently trained, it can generate new, entirely synthetic audio that closely mimics the target’s voice. This replication is so accurate that it can be challenging for the human ear to distinguish between the cloned voice and the original.

How Can You Spot Signs of Voice Cloning?

Recognizing the common signs of voice cloning is essential for individuals to safeguard themselves from potential threats. Here is what to look out for if you suspect you’ve come across an audio deepfake.

• Unnatural Intonations: Cloned voices may exhibit robotic or unnatural intonations, lacking the subtle variations and emotional nuances present in authentic human speech.

• Anomalies in Familiar Voices: Fraudsters leveraging voice cloning may struggle to perfectly replicate the unique speech patterns of a family member or trusted individual. If the voice on the phone doesn’t align with your grandmother’s usual way of speaking, such as peculiar intonations or unexpected language choices, proceed with caution.

• Inorganic Flow of Conversation: Cloned voices might exhibit a stilted flow, especially in unscripted and dynamic interactions, as voice cloning can sometimes encounter challenges in maintaining natural conversational cadence.

• Inconsistencies in Speech Patterns: Voice cloning relies on analyzing existing audio data, and discrepancies may arise when attempting to replicate spontaneous, unrehearsed speech. Sudden shifts in pitch, rhythm, or pronunciation may indicate a potential voice cloning attempt.

• Overly Precise Enunciation: Voice cloning algorithms may overemphasize precision in enunciation, resulting in a speech pattern that sounds overly polished or meticulous.

• Abrupt Tone Shifts: Cloned voices may struggle to seamlessly transition between different tones or moods within a conversation. Red flags include abrupt shifts from formal to informal language or sudden changes in emotional tone.

• Background Noise Inconsistencies: Authentic voices often come with background noise that is consistent with the environment. In voice cloning attempts, inconsistencies in background noise may arise, suggesting that the audio has been manipulated or synthesized.

Technological Solutions to Voice Cloning

Staying ahead of the curve requires leveraging cutting-edge tools and technologies like advanced voice analysis software and real-time voice authentication systems to detect voice cloning.

At DeepMedia, our commitment to addressing this challenge led to the creation of DeepID, an advanced deepfake detection platform designed specifically to identify vocal cloning and audio manipulation.

DeepID can actually take an audio, extract the voices from that piece of content automatically and then run it through our detection algorithms. Our detection algorithms have been trained on millions of both real and fake samples across 50 different languages and have been able to determine with 99.5% accuracy whether something is real or whether it has been manipulated using an AI in some way.

We’ve also been contracted by the Pentagon, as revealed in an interview with Fox Business, to build machine learning algorithms that are able to detect synthetically generated or modified voices across every major language, across races, ages and genders. The ultimate goal is to transform this AI into a versatile platform seamlessly integrated into the Department of Defense.

Users around the world are encouraged to sign up for DeepID here where they can upload up to ten audio video images or texts a day at no cost.

Having free access to deepfake detection is a powerful step toward safeguarding your digital presence and protecting the authenticity of your voice and identity in an era where trust and security are paramount.