Sunday, 19 May 2024 04:50

Scientists develop device that can detect when someone is sarcastic

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  • Experts have developed a device that can detect when someone is sarcastic
  • It works by examining the pitch, talking rate and energy in speech 

Our friends from across the pond have been known to struggle with British sarcasm on occasion.

But improved Anglo-American relations may be on the horizon, as experts have developed a device that can detect when someone is being sarcastic.

A team from the University of Groningen have created an algorithm that analyses someone's speech to work out if they are using irony.

It works by examining the pitch, talking rate and energy in speech, and then transcribing the speech into text for it to be analysed further for language cues.

'We extracted acoustic parameters such as pitch, speaking rate, and energy from speech, then used Automatic Speech Recognition to transcribe the speech into text for sentiment analysis,' author Xiyuan Gao said.

'Next, we assigned emoticons to each speech segment, reflecting its emotional content.

'By integrating these multimodal cues into a machine learning algorithm, our approach leverages the combined strengths of auditory and textual information along with emoticons for a comprehensive analysis.'

Sarcasm – which Oscar Wilde once described as the lowest form of wit but the highest form of intelligence – is notoriously tricky to convey through text and, even in person, it can be easily misinterpreted.

The team said they are optimistic about the performance of their algorithm, but are already looking for ways to improve it further.

'There are a rage of expressions and gestures people use to highlight sarcastic elements in speech,' Ms Gao added.

These need to be better integrated into our project. In addition, we would like to include more languages and adopt developing sarcasm recognition techniques.'

Sentiment analysis, which focuses on text, is already used for detecting online hate speech and gathering online customer opinions.

Meanwhile emotion recognition, based on speech, can be applied to AI-assisted healthcare, the team said.



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