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> I wonder if the ZDF gave its approval for it being used for LLM training though? I am pretty sure they didn't get asked.
Just like the people forced to pay for ZDF under threat of imprisonment.
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ُThe Arabic text is the translator's self credit "Translated by Nancy Qanfar"
And the German is “subtitles of [public broadcaster] for [content network], 2017 I'm not sure this is really overfitting, the network does exactly what the training data demands. According to the training data silence art the end transcribes to a copyright notice or subtitle credits
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Indeed, with another model I would get persistent transcriptions of silent parts into 'Thanks for watching!' or '[MUSIC]'. Pretty dumb that this failure mode wasn't caught in some QA process, and there are now multiple transcription models suffering from the same issue. Having silent parts in your input audio seems like it should be a very common occurrence...
When I was taught mathematics, the zero value was always considered the most important edge case. You prove something for N=0 (or N=1), then for N=M+1. It's even more important in audio DSP: processing near-zeroes can end up being extremely CPU intensive, look up denormal/subnormal floats.
Quite a lot of algorithms use some form of division and zero is the only number in our typical structures (Z, Q, R, C), that cannot be used to divide with.
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When I was taught mathematics, the zero value was always considered the most important edge case. You prove something for N=0 (or N=1), then for N=M+1. It's even more important in audio DSP: processing near-zeroes can end up being extremely CPU intensive, look up denormal/subnormal floats.
Yeah, I studied mathematics (algebra and number theory) and zero is the point, often sporting discontinuities, or weird asymptotic behavior. Quite a lot of algorithms use some form of division and zero is the only number in our typical structures (Z, Q, R, C), that cannot be used to divide with.
Error: division by please upvote, share and like!