2/13/2023 0 Comments Human benchmark test![]() ![]() This is my computer but let's just see how i do 30 targets as quickly as you can was that good or bad i think average is 450. okay whatever 204 that's not bad i'm 25 years old let me be a boomer i don't really know how this works memorize the pattern was that oh this is like the among us one up uh uh uh okay whoa whoa whoa whoa whoa whoa whoa whoa whoa whoa whoa whoa whoa whoa it's getting big it's getting big okay it's it's like a pattern down up okay no wait it's over okay i really thought i was about to go off hit 30 targets as quickly as you can okay i should do the best out of this than most of my roommates because. INTRODUCTION Automatic language identification, the problem of recognizing what language is being spoken, is a challenging research problem with important real-w.Today we are doing a test with all of my roommates i'm challenging them all to uh the human benchmark quiz there's ten different quizzes in total or think nine eight actually there it is final number uh that texts your reaction times your memory your aim your number memory your verbal memory chimp test typing and visual memory uh and i have all of my roommates slime aiden nick and cutie who i'm gonna challenge and whoever places the best in five of these eight challenges is gonna win 500 straight up i'm gonna give them 500 i'm going to try it first i'm just going to go through it i'm just going to go through them i'm going to be the guinea pig i'll see how i do reaction time when the box turns green click as quickly as you can okay i'm like twitching no oh my god okay i thought that was fast i think i have to do five total for them to get a a data point okay all right one more last one i want to get under 200. Statistical analyses of our results indicate that duration of the excerpt, familiarity with the language, and number of languages known are important factors affecting a subject's performance on the identification task. The subject population consisted of 10 native speakers of English and 2 speakers from each of the remaining 9 languages. In an effort to provide benchmarks for evaluating machine performance, we conducted perceptual experiments on 1-, 2-, 4- and 6-second excerpts of telephone speech excised from spontaneous speech utterances in this corpus. The advent of a public-domain ten-language corpus of telephone speech has made the evaluation of different approaches to automatic language identification feasible. There has been renewed interest in the field of automatic language identification over the past two years.
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