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AI to alter Indian call center worker voices to make them sound more American

Artificial intelligence is being incorporated across a large number of industries in the world, and will now even be used in call centers.

The world’s biggest call center operator, Teleperformance SE, will be utilizing AI to help make the Indian accent of their employees more palatable for those receiving the calls. A TechSpot report on the idea reveals that the AI model will analyze speech and work to modify it to match whatever accent it is programmed to duplicate. It will also preserve the original voice and emotion of the human speaker, simply aiming to make the accent less difficult to understand.

Deputy Chief Executive Officer Thomas Mackenbrock explained the goal to Bloomberg.

“When you have an Indian agent on the line, sometimes it’s hard to hear, to understand. [This technology can] neutralize the accent of the Indian speaker with zero latency, [creates] more intimacy, increases the customer satisfaction, and reduces the average handling time,” he said.

More advanced versions of this will even be able to “transcribe the spoken words into text, accounting for various accents and speech patterns.” Once the user’s voice is fully analyzed for accent and speech pattern, the technology will get to word modifying any hard-to-understand parts.

“During the conversion, the software modifies intonation, stress patterns, and phoneme pronunciation to align with the target accent. The system employs text-to-speech (TTS) technology to synthesize the phonetic pattern and convert the text into a synthesized voice that maintains the speaker’s original tone, emotion, and identity,” the TechSpot article explains.

The company’s client base already includes some massive names including Apple, TikTok, and Samsung Electronics, and is part of the larger parent company Teleperformance AI. This business is scheduled to invest over $100 million in artificial intelligence partnerships in the next year.

X users considered the ramifications:

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Sierra Marlee
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