Trying it Out5:10 with Ben Jakuben
The best way to understand what you can do with various Watson services is to try them out!
For starters, let's check out a website that lets you explore Watson services 0:00 right in the browser, without writing in any code. 0:03 If you search for Watson API services or click on the link in the teacher's notes. 0:06 You will come to this page that lists all the services currently available on 0:10 the Watson Platform. 0:14 So here we have some services related to conversation. 0:15 And some forward discovery and if we keep scrolling down we can see 0:19 computer vision and speech, language, and finally empathy. 0:24 As you could see there is a lot of computer empower available here. 0:29 The goal of these course, is to get you started some common and useful examples. 0:32 But there's much more available for you to use to solve different kinds of problems. 0:36 We encourage you to test a lot of these out, but 0:40 let's check out the Tone Analyzer here at the bottom. 0:42 So the Tone Analyzer service understands emotions and communication style in text. 0:47 So this means if I give it the text, I'm happy, it will detect a positive tone. 0:53 Amen, exactly how does the tone analyzer 0:57 determine human emotion from speech or text? 0:59 >> That's a great question, Ben. 1:03 We employed psychologists who use the big five personality traits. 1:05 Openness, conscientious, extraversion, agreeableness, 1:11 neuroticism, OCEAN, to be exact. 1:14 What they did is they collected lot of texts and they analyzed that text, 1:18 classified it, and they placed it within those buckets. 1:23 Each that they thought were appropriate to a particular tone that depicted 1:28 one of the big part personality traits. 1:34 From there on once Watson comes across an article, a text, 1:36 a paragraph, a noun phrase one that it hasn't' seen before. 1:41 It is able to then classify it and 1:45 come up with derivatives of those five such as joy, confidence, and 1:49 anger and hence depict the tone of the written or the spoken word. 1:53 >> It's incredible really. 2:00 And again, all this work is done behind the scenes to train these services and 2:01 make them available. 2:05 So when we're using them, 2:06 it's got all this information underneath that's ready for us. 2:07 >> Absolutely, yes. 2:11 >> So yeah, let's continue with our example here. 2:12 If we click on the view demo button, 2:15 then we come to a page that is pre-loaded with some samples. 2:17 So here we have some Tweets, Online Reviews, Email messages, etc. 2:21 And the first one in here is a series of tweets about people who are not happy 2:25 about new phone. 2:29 All right, so let's analyze this and see how it goes. 2:30 Click on the button here, all right. 2:33 So we get a document level summary, right, and it's showing us that there is some 2:35 anger, fear, and some confidence as the main tones present in this text. 2:39 And if we scroll down a little bit, we get down to the sentence level. 2:44 And we can see which sentences in the text match the different tones. 2:47 So if I click on anger, there we are, highlighted in red, 2:52 there's some angry sentences, some angry tweets about the phone. 2:55 Same thing if I click on tentative, nothing shows up. 2:58 If I try fear, got a sentence there at the bottom, about a fearful sentence. 3:02 So if we scroll back up, we can also enter our own text for analysis too. 3:07 I'm going to paste in a message I sent the teaching team recently. 3:11 So click your own text come in here and paste. 3:14 And let's see, yep, okay. 3:20 So if I analyze this. 3:21 Let's take a look, how did I do? 3:23 All right, so the tone analyzer is telling me that it detected joyful tones and 3:25 tentative tones. 3:30 If we click on each down at the sentence level we can see certain things, 3:32 the same things was detected as joyful. 3:37 If I click on tentative I can see some examples here where 3:40 we can see that the color here matches the, 3:44 it's a slightly less confident reading of this text. 3:46 So even the Tone Analyzer itself is tentative in its analysis here. 3:49 And one of the fun things that you suggested that I do is paste in some 3:55 angry text as well. 3:59 So I'm going to just here in the middle, insert some angry text and 4:00 analyze it again. 4:04 And now at the bottom, sure enough we got some angry passages. 4:06 And if I click on it, and scroll for the red one, you can not only see not only 4:10 angry but also detected some sadness which is interesting. 4:14 Two different passages, 4:18 there were different levels of confidence in how sad they were. 4:19 The Watson API documentation defines all of these interpretations. 4:23 And you can check it out using the link in teacher's notes. 4:27 You will definitely wanna refer to the docs for 4:29 each service that you wanna use in your apps. 4:32 Note that these API docs have sample code in multiple languages 4:34 right here on the right side. 4:38 This is some of the best documentation that I've ever seen. 4:40 You should plug in some things you have written, like emails or tweets and 4:43 see what the results are. 4:46 It's amazing. 4:47 >> So try some things out grab an excerpt from a sad song, 4:49 copy paste that into Tone Analyzer. 4:53 The one that I do most often is actually take a snippet of my email or 4:56 the entire email. 5:00 And I can't tell you how many times that has stopped me from sending the email 5:01 before I erase all the red and make it look blue. 5:06
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