h a l f b a k e r yNeural Knotwork
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Say words question you take. Put give too much answer very very.
Advertisement same same good very I give. Not waste.
Too much benefit is good. I take much information inside. Then, insufficient good very. I come back have same same. Learn speech not necessary even construct. They five.
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Annotation:
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I too five. We have so much in common. |
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baked on most instruction leaflets I come across. |
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So if I'm reading this idea right it's "gibberish is funny ha ha, so make a chatbot that speaks gibberish" Am I reading this idea right? |
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I don't think it's quite gibberish, or not necessarily at least. I'm pretty sure linguists can predict the type of errors and mispronunciations someone will make in a second language based on vocal and grammatical habits from their first language. Classic ones are mixing up genders when coming from a language that doesn't use gendered pronouns. Or confusing the sound of L and R when coming from a language that don't distinguish the sounds. |
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But of course not all mistakes are predictable, so some randomness (gibberish) should be sprinkled in. I knew a Chinese real estate agent in the US who somehow learned the word "sewage" incorrectly and would constantly refer to it as "sausage". I couldn't correct him without laughing so I just let it be. |
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All your base are belong to us. |
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Thanks [a1]. Better in Yodish, it sounds |
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