AI Deconstructs a High Stakes Poker Bluff

Poker pros are experienced in spotting a bluff. Can Artificial Intelligence measure up? We take a look at an interesting bluff between Charlie Carrel and Lean Tsoukernik. What are the ‘tells’ spotted by AI and did the pro spot them?

The Texas Hold ‘Em table falls silent as Charlie Carrel slides his large stack of chips forward. “At the risk of looking silly on TV, I bet 650,000,” he declares and winces. The wince is a bit unnatural and hints at acting. His opponent, Leon Tsoukernik, coolly responds “We’re in business” while pushing chips to match the bet.

YouTube video Link. Key segment commences at 2:40

Carrel then proclaims “That is the face I wanted to see ladies and gentlemen, this is the face of Leon without a straight flush!” This is the critical juncture of the bluff as Carrel is trying to represent that he has either of the two cards that can beat Leon: the Ace or Ten of spades.

Using voice analytics AI analyzed the verbal patterns, vocal cues, and word choices behind this poker table drama. The results reveal subtle, science-backed signals separating truth from deception in this high stakes hand.

Deception Detectors – Vocal Cues of a Bluff

When executing a skillful bluff, the voice can betray even seasoned poker faces. Nervousness and false bravado lead to small changes imperceptible to the naked ear. Yet voice analysis detects these clues with sharp accuracy.

Carrel’s vocal pitch surged as he boasted of Leon’s “face without a straight flush.” But micro-tremors and wavering vocal stability told a contradictory

When questioned on his bluff, Charlie’s speech rate spiked and pitch jumped erratically. Voice analysis revealed deception through emotional stress leaks – all while player Leon kept a calm facade.

His opponent Leon maintained an even keel vocally. Steady shimmer, jitter, and slow speech rate suggested truthfulness. The analytics aligned with Leon’s stoic body language during the hand.

Cracking Under Pressure – Word Choices and Bluffing

Even crafted words give away deceivers. Carrel’s peculiar phrasing revealed subtle psychological insights.

Saying his bet came “at the risk of looking silly” minimized the shame of being caught bluffing. His focus on “looking silly on TV” shifted attention away from the lie itself.

When Carrel insisted Leon’s straight flush was “not possible,” his strained pitch and accelerated speech rate telegraphed desperation. Backpedaling rapidly when challenged, he feigned confusion – “Why?”

In contrast, Leon stuck to simple, direct questions. His vocabulary raised no red flags. Leon let the pressure of silence force his opponent to act first.

Science Shows the Cards – Voice Analysis Detects Deception

Voice analysis provides a wealth of clues to uncover deceit in high stakes games. Carrel’s bluff failed the vocal test in multiple ways, while Leon’s truthfulness consistently held up.

Next time you suspect a bluff, don’t go with your gut – let the data do the detective work. Subtle voice cues and speech patterns separate truth from lies if you know where to look.

With the right analytics, you can confidently call anyone’s bluff, even professional poker stars. You’ll know their truth…from the mouth out.

© 2023 Speech Craft Analytics. All Rights Reserved.

David Pope is Chief Data Scientist at Speech Craft Analytics

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