How Artificial Intelligence Listens to and Analyzes Phone Calls?

Tehran - BORNA - One of the most striking areas of development is the use of AI to listen to and reconstruct phone conversations. Until recently, phone tapping was largely limited to security agencies with specialized equipment. Today, however, the combination of AI with relatively simple tools, such as millimeter-wave (mmWave) radars, has opened the door to capturing and reconstructing conversations from several meters away even without direct access to a device.

This article explores two main aspects of this issue: (1) the technical progress of AI-driven phone tapping using radar technology, and (2) the legal and organizational use of AI to analyze and monitor calls in customer service centers.

Remote Eavesdropping with AI

mmWave Technology and Voice Reconstruction

In 2024, a research team at Penn State University demonstrated that the tiny vibrations of a smartphone speaker during a call could be detected from a distance of up to three meters using millimeter-wave radar. These waves, which are already used in fields such as 5G communications and 3D scanning, have opened up new possibilities in information security when paired with AI models.

The project, known as WirelessTap, works in two stages:

Capturing the vibrations of the phone using mmWave radar.

Reconstructing speech using speech recognition models such as OpenAI’s Whisper and adaptive learning techniques like Low-Rank Adaptation.

The researchers were able to transcribe conversations with an accuracy rate close to 60% in controlled laboratory conditions.

Earlier, in a 2022 study, another team reconstructed ten pre-selected words with 83% accuracy. According to a paper published on arXiv, the system’s word accuracy stood at 44.74%, while character accuracy reached 62.52% in tests conducted at distances of 25 to 125 centimeters.

The researchers emphasized that the technology is still in its early stages, and factors such as environmental noise, phone positioning, or surrounding surfaces significantly affect performance.

Security Threats

A 60% accuracy rate may not sound alarming at first. However, given the rapid pace of AI development, this capability could soon become far more precise. If commercialized or used covertly, anyone within a few meters of a phone call could potentially capture its contents without touching the device posing a serious threat to both personal privacy and organizational security.

Legal Applications: AI in Call Analysis

On the other side of the spectrum, AI is increasingly being used for positive applications particularly in call centers, where it enhances service quality and efficiency.

Automated Call Monitoring

Traditionally, call quality was evaluated manually, with supervisors listening to a fraction of recorded calls. This method was slow, resource-intensive, and prone to human error. Today, AI tools can automatically monitor 100% of calls, evaluating quality, tone, customer satisfaction, and even emotions.

Sentiment and Behavior Analysis

Speech analytics technologies use machine learning models to detect keywords, language patterns, and even vocal tone. These insights allow AI systems to classify emotions such as anger, frustration, satisfaction, or excitement.

For instance, the insurance company MetLife employs a system called Cogito. This software analyzes a customer’s voice in real time and alerts the call agent if it detects stress or dissatisfaction, prompting them to adjust their tone or communication strategy.

Organizational Benefits

Comprehensive Monitoring: AI evaluates every call, unlike traditional sampling methods.

Reduced Human Error: Analysis is data-driven rather than subjective.

Real-Time Feedback: Agents receive instant guidance during conversations.

Business Insights: Organizations can identify recurring issues and trends, improving customer service strategies.

According to CallCriteria, AI-based call scoring systems enable call centers to process massive volumes of conversations without hiring additional staff. A study cited by Time magazine also reported that AI use in call centers reduced customer churn and improved satisfaction rates.

A Double-Edged Sword

AI in telephony is a double-edged sword. On one hand, projects such as WirelessTap highlight the potential for phone conversations to be intercepted from a distance raising serious privacy concerns. On the other, the very same technologies are improving communication quality, customer experience, and organizational performance in legitimate contexts.

The future of these applications will depend heavily on legislation and ethical governance. If properly regulated, AI could become a valuable tool for enhancing human communication. Without oversight, however, it risks becoming a powerful weapon against personal freedom and privacy.

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