When someone gives a talk or a performance or a lecture, people talk about “the energy in the room”. Everyone can tell when something magical is happening, or conversely, when the whole thing is falling flat.<\/p>\n
This isn’t merely about counting laughs. After all, most of us can also tell when an audience is enjoying a serious drama, or an academic lecture.<\/p>\n
So here’s an interesting challenge for artificial intelligence: Could we design an algorithm that is able to sense the energy in the room?<\/p>\n
One approach would be to construct the algorithm as a trainable neural net. Volunteers in the audience would indicate to a computer a high or low score that reflects their own human sense of how well a performance is being received, and a pattern matching algorithm would “learn” how to associate that score with cues from the audience.<\/p>\n
Yet the problem remains: What are valid audience cues? Breathing? Whispering? Facial expressions? People squirming in their seats? What factors are we ourselves using to “sense” an audience’s mood?<\/p>\n
I’m not sure anybody really knows the answer to that.<\/p>\n","protected":false},"excerpt":{"rendered":"
When someone gives a talk or a performance or a lecture, people talk about “the energy in the room”. Everyone can tell when something magical is happening, or conversely, when the whole thing is falling flat. This isn’t merely about counting laughs. After all, most of us can also tell when an audience is enjoying … Continue reading “The energy in the room”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/posts\/14483"}],"collection":[{"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14483"}],"version-history":[{"count":1,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/posts\/14483\/revisions"}],"predecessor-version":[{"id":14484,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=\/wp\/v2\/posts\/14483\/revisions\/14484"}],"wp:attachment":[{"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14483"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14483"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/blog.kenperlin.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14483"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}