This video introduces MICASE, a searchable collection of the transcripts of real-life, spoken language on the University of Michigan campus. Most of the original audio files are available for download too. So what can you do with MICASE? Well, first, let's look at listening. These raw listening materials are a great source for practicing listening strategically. >> [INAUDIBLE] >> Sorry, if you want to get the old book. >> That's okay. >> Okay. >> You can, for example, listen for emphasized words with high content, or listen for the intonation that signals uncertainty or confidence, incomplete or complete thoughts. Let's look at an example of the transcript that goes with that particular audio file. It's a biochemistry study group. So I'm going to choose Speech Event Type, Study Group. And we'll get a list of all the study groups. And we want to look at the transcript of the Biochemistry Study Group. So a little orientation to what we're seeing here. Here's the title of what happened here. The code that you see all over this database for this transcript. Um They rate the interactivity as highly interactive, they tell you how many participants are there, and how long it is. If we listen to the sound file and look at the transcript, we can identify particular features of speech. We can find uncertainty with rising tones, for example. >> I think this one's the one that leaves. We can find confidence with rise fall tones. >> So then you have another carbon, leaving, like the step name is called the same oxidase decarboxylation. But it's a very different enzyme, has different substrate. >> And we can see examples of emphasis with strong rising tones, and sustained vowels on plants. Lipids and glucose. >> So what plants can do is they can take lipids and turn them into glucose. >> On the sound file side, you can download a sound file by right clicking on it. And with that downloaded sound file, you can try to understand a bit of fast reduced speech, use other software to playback that sound file more slowly. And check your understanding against the carefully constructed transcript. We can also use MICASE for finding vocabulary for spoken genres of communication. The browse interface is again useful here. By looking at the transcripts of office hours encounters for example, we can see what words instructors use to welcome students. Or to find out what they want to accomplish in office hours, or to say goodbye. Similarly we could look at the ends of class sessions to see how instructors signal that class is over. And see what kinds of content is regularly announced at the end of class. MICASE can also illustrate how turn taking and collaborative decision making can look in a study group or project meeting. In this economics office hour an instructor is visited by several undergraduates as well as one graduate student instructor who's a teaching assistant for the class. And someone who stops by looking for a person in a different department. Each speaker is assigned a number. S1, S2, S3 as they enter the conversation. By searching for these codes on the page, we can see what words are used at the beginning of each interaction. These greetings may look different than greetings we see in a text book. Good morning, how are you? Usually doesn't show up as a welcome in office hours. So here at the start we see that the recording and transcript started after the first conversation did. Somebody's in the middle of a sentence. So S1 and S2 are already talking. We should skip to S3. So I'm going to search like I would for on any web page for S3. And then here at the first instance of S3, I see a new conversation is started and right before that I can see the instructor. Speaks and this is her greeting, hi were you waiting to see me for office hours? Now we can look for S4. So Professor Gaston is speaking here at S2 in the middle of the page. And notice there's a student waiting presumably. And says hi, how are you? Be with you in just a minute. In this manner we can go through this transcript pretty quickly and collect different examples of how the instructor greets students during her office hours. We can see how conversations with multiple people go. um I happen to know that later on in this transcript, students 7 and 8 are chatting together before they get the instructor's attention. Sorry, student 7 and 5 are chatting together before they get the instructor's attention. And then their background conversation ends. And the instructor pays attention to them and says okay, we're going to start. Hey, I've got a crowd. Why don't you grab a chair and join us? Your name is? And this is how she interacts with multiple people in a greeting. So supposing we want to look at this vocabulary more closely, specifically the use of grab. Here, instead of the browse interface, the search interface is particularly useful to us. We can type in the word grab and search across the whole database. Where we find that there are 28 uses of this verb in 21 different events. And here we see there's just a lot of different usage. It can be a little hard to navigate what exactly we're seeing. So the database offers a way of organizing it to sort results. If we sort results to the right of the word grab If we sort results to the right of the word grab. If we sort results to the right of the word grab. We'll be able to see the kinds of things that get grabbed. 1R, 2R, and 3R, I mean one word to the right, then two words to the right, then three words to the right. So we get grab a calculator is the first thing in alphabetical order. Then we have two examples of grab a chair, grab a microphone, two examples of grab a net. But we can see over here that that's a lab recording. So we can see how this word grab patterns with its close friends and neighbors. Scrolling through these examples, you can see that there's lots of small physical items like pens and cameras that one can grab. But there are also intangible things like the easy stuff, or problems, or life that one can grab. I don't see large enough numbers of any repeated example to get a sense of a common idiom with grab, but this is a relatively small database. So such idioms may well exist without us seeing evidence of them here. If we're puzzled about a particular example, we can click on it to see more context. Let's look at this one. Here's a little one too. You want to grab that one? Small mouth and I may wonder, what is a small mouth? I have a little bit of a clue over here In the code that this is a lab. So I begin to guess that maybe it's a kind of jar or beaker in a chemistry or biology lab. I can click the view button just to see a little bit more context, rather than the whole transcript which can be kind of overwhelming. So let's click on view and test my hypothesis that we are looking for a small mouth jar. And so here we see, this I know nice bass Spottail, Spottail Spottail, Spottail, oh here is a little one too you want to grab that one? Smallmouth? Largemouth? [LAUGH] Largemouth, Smallmouth two perch, one Largemouth. So here I've discovered that this actually a biology of fishes field lab and that the Smallmouth is a kind of fish. So okay, we can grab fish too. While it can be time consuming to explore language use in this data. The rewards are substantial. Why not just ask a friend how a phrase is use? That will be a lot faster, right? Well, I'm like the intuition of a single fluent speaker of English. A database of many speakers provides a window into the range of actual language use of a whole community. And rather than one person explaining how something works, we can get 4,439 examples of how something works. Or in the case of grab, 28.
