Fraport USA’s Post

The Challenges of Voice recognition technology

That's how you start th year mate

in a multicultural working environment, an LLM with varying accent, dialect and languages will be crucial for this. though it's neither efficient nor effective

Prepare for the coming of AI voice recognition 😆😆😆😆😆😆😆

As AI systems become more sophisticated at understanding natural language, new challenges arise in handling the nuances between different dialects and locales. For example, an American English speaker would spell "color" while someone from the UK would spell "colour." Similarly, a drug may have completely different names in the US versus the UK or Australia. These differences can trip up AI systems that aren't specifically tuned to handle multiple dialects. It's like asking "what shade of gray is this?" without any additional context - there's no one right answer. The system needs more information to home in on the correct meaning. To overcome this, AI training data needs to include diverse sources from different English-speaking countries. The models then need to learn when to switch contexts based on cues like spelling variations, vocab choice, etc. It's not impossible, but it requires thoughtful tuning and testing to ensure the AI understands the many nuances between flavors of English. The same approach applies for non-English languages. Training datasets and queries need to be tailored to the specific locales the AI will deal with. There's no one-size-fits-all model - customization is key. With careful iteration, we can develop AI flexible enough to smoothly transition between dialects and sub-languages. But it takes consideration of the unique challenges around language variation. #ai #artificialintelliegence

Scottish English ;)

Funny clip on a serious issue of technology: what if you have a problem (eg accent, unusual situation/unique circumstance) and you are forced to deal with AI or automated response systems. Thanks Alvin Foo for posting.

voice recognition

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The future of AI!