Author Archives: Maria Gouskova

How to Make a .Collection File

A Praat .Collection file allows you to save all the audio files and text grids that go with them into a single file. It’s a bit like a zip file, except it isn’t compressed. It also, conveniently, keep the order in which the original audio files and text grids (and any other objects) appeared in your Praat object window.

  1. Make sure all your objects–sound files, text grids, etc. are named what you want them to be named, and that they appear in the correct order. For another person looking at your files, it’s most convenient if your sound file is adjacent to the corresponding text grid in the Praat object window. Here, you can see that I have audio files and text grids paired by name:

2. Select all the objects in the Praat window that you want to save together. In my operating system (Linux), Ctrl+A selects all the objects. Windows is probably similar. In Mac OS, it will be the Command key.

3. Go to “Save” and select “Save as binary file…”:

4. Give the file some name that will make sense to you later. The default is “praat.Collection”. Hit “save”.

5. To reopen the .Collection file, first open Praat, then go to “Open>Read from file” and navigate to wherever you originally saved it. If all went well, you will see a window that looks exactly like step 2 above.

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FAQ

I often get email inquiries from people interested in our PhD program, often with a CV or a writing sample attached and a request that I look at the file. The way our program does admissions, no one faculty member has power over who gets in. There is a detailed explanation of this on our department’s FAQ for prospective applicants.

If you think that your research is a close match to my interests (morphology and phonology), of course I will consider advising you if you get accepted–but writing to me instead of applying to the program is not going to help you get in. Instead, I recommend that you study the FAQ closely. When you submit your application, make sure to check my name as someone who influenced your decision to apply to NYU Linguistics, and I will read your file then. Good luck, and thank you for your interest in our program.

Maria

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Linguist names

The goal of this page is collect some names of linguists whose pronunciations are non-obvious.


My name

The audio files and transcriptions for my name are here. Please do not call me Masha. There are Russian women named Maria who go by Masha in professional contexts; I am not one of them. Relatedly, did you know that Michael Becker and Misha Becker are not the same person?


Everyone else’s names: notes

People who are linked without comment have included IPA transcriptions of their name pronunciations on their websites. NB: If people pronounce your name differently from how you’d like it to be pronounced, or if you’ve ever been asked how to pronounce your name, that’s a hint that you should put that information on your website. It is more likely to reach the target audience if it’s on your site than on mine. Roman Jakobson–you’re off the hook on this one.

Transcription notes:

  • the bias is towards anglicized pronunciations here, with some sloppiness in whether vowels are reduced. The focus is on stress placement and non-obvious consonant and vowel qualities, or vowels you might think are silent that aren’t.
  • I offer neither explanation nor apology for my inconsistent use of [r] vs. [ɹ] vs. [ɚ].
  • I mark stresses before the stressed vowels because life is too short to try to figure out the syllabification in some of these names.
  • In a few names, there is a dorsal fricative. I decided to leave that as [x] in the transcriptions, as many American linguists seem comfortable with approximating it. If you are not one of them, my prescriptive suggestion would be to substitute [h]; to my ears it sounds like the next best thing. Maybe a [k] if Ident[place]>>Ident[continuant] for you.

If you have a request or a correction, send me an email!


A

John Alderete: [ɑldərˈɛɾi] not [ɑldərɛt]

Scott AnderBois: [ˈændɚbwɑ]

Amalia Arvaniti: [amalˈia arvanˈiti]

B

William Badecker: [b’eɪɾəkɚ]

Eric Baković

Alicia Beckford Wassink: [əlˈisiə] not [əlˈiʃə].

Gašper Beguš: [gˈaʃpɚ bˈɛɡuʃ]

Stefan Benus (Štefan Beňuš)

Christina Bethin: [bətˈin] not [bˈɛθən]

Claire Bowern: [bˈoʊɚn]

David Bowie: [bˈu.i], like the town in Maryland not like the singer

Adrian Brasoveanu: [braʃovˈanu]

Canaan Breiss: [kˈeɪnən braɪs]

Marisa Brook: [mərˈisə]

Mary Bucholtz: [bˈʌkəlts]

Rachel Burdin

C

Pavel Caha: [tsˈɑhə] or [sˈɑhə], not [kɑhə] or [tʃahə]

Dustin Chacón: [tʃakˈon] not [ʃ…]

Vincent Chanethom

Ioana Chitoran: [ioˈɑnə kitsorˈɑn]

Eleanor Chodroff

Catherine Chvany: [tʃvˈɑni]; Hypocoristic: [kˈatʲə].

Andries Coetzee

Uriel Cohen Priva: [ˈuriəl kˈoʊən prˈivə] not [juriəl]!

Ailís Cournane

Meg Cychosz

Patricia Cukor-Avila: [sˈukɚ ˈævɪlə]

D

Éva Dékány

Derek Denis: [ˈdɛnɪs]

Katherine Demuth: [dˈiməθ]

Ray Dougherty: [d’ɑgɚti]. Like other Irish surnames, the Anglicization of this one is variable

Karthik Durvasula

E

Masha (Maria) Esipova

F

Donka Farkas: [fˈɑrkɑʃ]

Matthew Faytak: [fˈeɪtˌæk]

Paul Foulkes: [faʊks]

Kathryn (Katie) Franich: [frˈænək]

Joseph Fruehwald: [dʒˈoʊsɨf frˈuːwɔld]

G

Adamantios Gafos: [adamˈɑntios gˈɑfəs] (or [ɣˈafos]). Hypocoristic: Diamandis [dˌiəməndˈis]

Mark Garellek

Anna Grabovac: [grˈɑbovak]

Vera Gribanova: [vˈɛrə ɡribˈɑnəvə]

John Gumperz: [ˈɡʌmpəɹz] [source]

H

Liliane Haegeman: [hˈɑxəmən] not [heɪɡə…]

Boris Harizanov: [bˈoris harizˈanov]

Stephanie Harves: [hˈɑrvəs] not [hˈɑrvz]

Martin Haspelmath

J

Roman Jakobson: [jəkabsˈon] or [jˈɑkəbsən], not [dʒeɪkəbsən]

Gaja Jarosz

Peter Jurgec: [jˈurgəts]

K

René Kager: [kˈɑxɚ] not [keɪdʒɚ]!

Roni Katzir: [rˈɔni kətsˈir]

Abigail Kaun: [kɑn]

Jaklin Kornfilt: [ʒaklˈin kˈɔrnfɪlt]

Jelena Krivokapić: [j’ɛlɛnə krivok’apitʃ]

L

William Labov: [ləbˈoʊv] (since people immediately started arguing with me on this, I’m including a citation to a source; 2006, Journal of English Linguistics 34:4)

Terry Langendoen: [lˈæŋɡəndən]

Beth Levin: [ləvˈin] (note stress location and vowel quality)

Erez Levon: [ˈɛɹɛz ˈlɛvɑn] not [əˈɹɛz ləˈvon]

Mark Liberman: [lˈɪbɚmən] not [lˈibɚmən]

Anna (Ania) Łubowicz: [wubˈovitʃ]

M

Sally McConnell-Ginet: [ʒɪˈne]

K.P. Mohanan: [mˈoʊhanan] not [moʊhˈænən]!

Marcin Morzycki

N

Naomi Nagy: [nˈeɪɡi]

Savithry Namboodiripad

Luiza Newlin-Łukowicz: [luˈiza nˈɛvlin wukˈovitʃ]

Máire Ní Chiosáin: [mˈɑrə nˈi xisˈɑn] — or [x’isɑn], depending on dialect, or even [mˠˈɑːrʲə nʲiː xʲˈisˠɑːnʲ] depending on your preferred level of pedanticism (I have also been given [kis’ɑn] but that has been challenged so I will leave all of these here and let you decide)

Yining Nie

Jennifer Nycz

O

Elinor Ochs: [oʊks]

David Odden: [oʊdən]

Cemil Orhan Orgun: [dʒemˈil orhˈan orɡˈun]

P

Joe Pater: [peɪɾɚ] not [pɑ…]

Charles Peirce: [pɚs]

Katya Pertsova: [pertsˈovə] not [pˈertsəvə]

Janet Pierrehumbert: [pieɹhˈʌmbɚt]

Glyne Piggott: [glɪn] not [ɡlaɪn]

Omer Preminger: [ˈoʊmɚ prˈɛməndʒɚ]; [ŋɡ] in German or Hebrew

Adam Przepiórkowski

R

Ezer Rasin

Yulia Rodina: [jˈuliə rˈodinə]

Marcos Rohena-Madrazo

Nicholas Rolle

Jerzy Rubach: [jˈeʒi rˈubax] not “Jersey”. You can try a retroflex ʐ, [jɛʐɨ]

Amanda Rysling

S

Elizabeth Sagey: [sˈeɪdʒi] not [seɪɡi]

Gillian Sankoff: [gˈɪliən sˈæŋkˌɑf] not [dʒɪliən]

Philippe Schlenker: [filˈip ʃlɛnkˈɛr] (note, final stresses in both)

James Scobbie: [skˈɑbi] not [skoʊbi]

Márton Sóskuthy: [ʃˈoʃkuti]

Michal Starke: [mˈixal ʃtˈarkə]

Robert Staubs: [stɑbz]

William Stokoe: [stoʊki]

Patrycja Strycharczuk: [patrˈitsjə strixˈartʃək] or [stri{h|k}ˈartʃək] (Polish: [patrˈɨtsja strɨxˈarʈʂuk])

Anna Szabolcsi: [ˈænə sˈɑboltʃi] (note, not [ɑnə])

Benedikt Szmrecsanyi

T

Sali Tagliamonte: [tˌæɡliəmˈɑnti]

Meredith Tamminga: [tˈæmɪŋɡə] not [təmˈɪŋɡə]

Anne-Michelle Tessier: [tˈɛsiˌeɪ] not [tɛsiɚ]

One Tlale Boyer: [ˈone tˈɑle bˈojɚ]

Peter Trudgill: [tɹˈʌdɡˌɪl] not [tɹʌdʒɪl]

V

Ljuba Veselinova: [liˈubə veselˈinəvə]

W

Gert Webelhuth: [vˈe:bəlhˌut]

Y

Charles Yang: [jɑŋ], not [jæŋ]/[jeŋ]

Z

Draga Zec: [drˈɑɡə zˈɛts]

Erik Zyman

Elizabeth Zsiga: [zˈigə]

Kie Zuraw: [kˈaɪ zˈurˌɑ] not [zurˈaʊ]

Acknowledgments

Special thanks to Laurel MacKenzie, who supplied many transcriptions and suggestions. Thanks also (in no particular order and without links, sorry) to Tricia Irwin, Wayles Browne, Steven Franks, Michael Becker, Ryan Bennett, Ailís Cournane, Greg Guy, Lisa Davidson, Anna Szabolcsi, and Emily Gasser for suggestions and transcription verification.

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Using Praat Scripts

Goal: Before you attempt to write your own Praat script, you will probably try to use one of the many existing scripts. This guide is not going to teach you how to write your own scripts, or even how to modify existing scripts in minor ways for your own needs. All it covers is how to use scripts that someone else wrote. It is intended for students in an introductory phonetics course, who usually have little to no background in working with scripts or programming languages.

The point of Praat scripting is to automate tasks, so you, the human, can do all the smart stuff, and leave the computer to do repetitive boring stuff. For example, suppose you are working on a study where your interest is in measuring durations of certain consonants. Praat cannot accurately label the edges of those consonants for you–that task falls under “smart stuff” that requires human eyes and ears. But Praat can rapidly collect the durations of labeled intervals from a TextGrid for you, if you prepare the right sort of TextGrid and tell Praat exactly what you want.

The most basic thing you will do with a Praat script is make it run and tell it to do something to a file you provide, and then save the result to your computer. The confidence builder exercise below talks you through that.

But first…

Praat vs. the internet and your phone

Praat cannot read your mind.

If you are like most students taking an introductory phonetics course right now (I’m writing in 2021), the internet has always existed for you, and it isn’t your mom’s internet of 2002. Most of the apps on your phone are fronts for web apps–they allow you to interact with a website or a distributed network. Thus, your familiarity with computers is intimately tied with how the internet has evolved. Websites and web apps are designed to try to read the user’s mind, and to fail gracefully in the face of typos and missing pages. They keep your stuff organized for you, so that you can search for pictures or music or videos and somehow always find it. All the magic is hidden. One side effect of this is that kids these days can’t find things on their computers.

By contrast, Praat was originally written in the late 1990s. It has been continually maintained, and features have been added to it, but its basic nature is very 90’s. It is meant for people who know their way around their computer and who understand how to get the computer to do things the old-fashioned way. The challenge before you, then, is to learn how to talk to a 90’s computer. You need to tell the computer exactly where stuff is. (You need to tell the computer the order in which to do things, too. If you’re working with existing scripts, as in this tutorial, you generally don’t have to worry about that.)

Another side effect of Praat’s not knowing how to read your mind is that you have to be very careful with typos and whitespace. (I’ll explain what “whitespace” means below.) Approximate is not good enough; you have to be precise. You need to be extremely attentive to detail.

You are eventually going to encounter some situations where things go wrong, but Praat doesn’t tell you why. See, Praat cannot read your mind, but you have to read its mind. This is what we call debugging. You need to decompose the situation that leads to failure into steps that you can change, one at a time, to isolate the step that is causing problems. This requires an analytic approach that can be a lot of fun, as long as you frame the problem correctly.

A confidence builder

Let’s try a simple script, which is known to run on a pre-chosen audio file. The script we’ll use is Mietta Lennes’s mark pauses, and the audio file is Newgatenovelist’s reading of Her Hair, a poem from the free Librivox project. You can hear the original mp3 at the linked page; here is the .wav file I made (I used ffmpeg). As a rule, you should be working with .wav files in Praat, not .mp3 files, because the time stamps in mp3 files are not accurate.

  1. First, go to your Desktop and make a folder there named pauses. [Mac instructions][Windows instructions]
  2. Save the .wav file to that folder. Once the file is on your computer, you can view its properties by right-clicking on it (Mac users, hit Control+click). The properties will give you the location of the file, as well as its size and other details.
  3. Download the script file to the same folder.
  4. Open Praat, and load the audio file into it as a LongSound object. To do this, from Praat, go to Open>Open long sound fIle. The newest sound object opened should be selected by default. If it isn’t, click on it to select it. This will become important in a sec.
  5. Now open the script: click on Praat>Open Praat script.... You’ll see a boring-looking text file, like this:
  6. Hit “Run”. You now see a dialog window called "Run script: Give the parameters for pause analysis."
  7. Okay, now it’s time to edit something. Pay attention! You need to change the path in the last field, the one called Save TextGrid file to folder:, to the location of your audio file. If you put it in pauses on your Desktop, then the path will end in Desktop/pauses/ if you’re on a Mac or Linux machine (or Chromebook?), and Desktop\pauses\ if you’re on Windows. The part before that will be your home directory; look at the path to the file as explained in step 2 if you don’t know how to find your home directory. The slash at the end of that is important–and if you make any typos, things will break.
  8. When you’re ready, hit OK. If you did everything correctly, you should see a white Praat Info window that says Ready! The TextGrid file was saved as /wherever/you/told/Praat/to/save/it.TextGrid. If not, well, it’s time to debug things, so read the rest of this page and come back to step 7.
  9. You should also be able to see a new TextGrid object in your Praat object window. Open it together with the sound file, and you’ll see that there is a TextGrid with a “sentence” level that has intervals marked. The intervals are silences longer than 0.6 seconds. Look at the Run script window again and you’ll see that this is a default value defined in the third field of that dialog. You can also figure out how the script identified pauses by looking at that window: there is an intensity threshold (59 decibels) that defines a pause.

Okay, so what was the point of that? If you look at Mietta Lennes’s other scripts, you begin to see how this might be useful. There is a script on that page that will label a TextGrid with labels from a text file. For example, your poem. You will need to edit the TextGrid to make sure that the pauses coincide with line breaks, but it’s a lot quicker to do than to doing it from scratch. In the case of this recording, you just need to remove some interval boundaries.

There is also a script that will save labeled intervals to separate audio files, and create matching TextGrids to boot. I hope you can see how that would be useful for the final project I’ve assigned you.

A random list of problems and solutions

  1. Many problems can be fixed by starting with a clean Praat session. Remove all objects from the Object window, and start afresh. Praat scripts often operate by putting objects in the window and doing stuff to them; if there are already objects there, and they are of the wrong type, it can break the script.
  2. Unable to save file“… If you get errors about files not being found, you messed up your path somehow. Maybe you left out a slash at the end of path, or added a slash when you shouldn’t have. Maybe you skipped a crucial directory in your path. Check everything–and use the information about file locations that you get from looking at their properties, as described above.
  3. Script works on some files but breaks on others. For scripts that are supposed to work on a bunch of files: if the script is working for some of your files and failing for others, you should examine closely those text grids where the script is having trouble. That will give you an idea of what could be going wrong (for example, one of the interval boundaries might be missing in that file, but not in the others–that can break a script.)
  4. The script is asking you to enter a non-zero value, and you don’t know what to enter. (The default value in the “save labeled intervals to wav files” script is 0.000, which I normally change to 0.0001.) Try a few different numbers and see what the output looks like. The script doesn’t modify your original data, so there’s no harm in experimenting. That’s how you learn what the script does.
  5. The script giving you undefined values for some of your intervals. This could be because you mis-segmented your text grids–if you placed the boundary on something that isn’t a vowel and has no formants to measure, then of course the script will not be able to measure your formants. (Ditto for intensity, possibly.) Solution: make sure your segmentation identifies vowels.
  6. Are you running the script on the wrong file? You’re having trouble running the formant/intensity/duration collecting script on your large data file with a single text grid. That’s because the script is intended for a bunch of small individual files paired with text grids. Make sure you read the homework instructions carefully, don’t skip steps.
  7. Empty results.txt file. This one has many causes, but probably the chief one is that you’re telling the script to look for files in the wrong location. Did you change the paths to ones for you computer, or did you leave them as the defaults that were already there? On a Mac, your path probably should start with “/Users”; on a Windows machine, with “C:”. The paths below are from my Linux machine; your paths will need to be different.
    1. collect_data_dialog
  8. The script break on files that have spaces in their names. Your labeled intervals have spaces in them. Your sound files and your text grid files do not have matching names, so the script chokes. What’s the solution? Respect whitespace! See below.
  9. You’re running your data collection script on empty text grids. This is another source of the “empty results.txt file” problem. Did you save the TextGrid files after you changed their contents? Remember, Praat doesn’t save files automatically for you, like other programs you’re used to. There is no autosave of changed objects in the Object Window. You have to overwrite the files in the directory where Praat is looking for annotated text grids.

Some other gotchas in Praat scripting

  • Praat itself will warn you if you try to overwrite an existing file, but a Praat script will not. Always test a script in such a way that there is no danger of it overwriting important work.
    • Solution: create a copy of the directory with your text grids and run the script on the copy, so there is no danger of screwing up your originals. If all goes well, you can delete the originals.
  • A Praat script might be configured to have a default file name for a text grid or an audio file it created, so if you want to save multiple audio files cut out of a single big audio file, it may overwrite the same file with new content without telling you.
    • Solution: If you end up with one file but you expected several, and the one file you see is the last file you expected to be created, then the answer to your problem lies in how files are named.
  • A typo in a key location will break things. There’s no solution here but to pay attention; see also below.
  • Praat will not give you interpretable error messages unless the script you’re running provided for them. Again, there’s no solution other than to be careful.
  • There are no helpful mouseover (or finger press) hints that explain what buttons do. Once you hit that “Run” button, you might be running a risk of losing stuff. So check everything many times before you run a script.
  • There might be technical problems with a particular measurement: for some acoustic analyses, the time window has to be of a certain length, so if your vowel, say, is too short, a Praat script measuring it will fail for inexplicable reasons.
    • Solution: attempt to do the measurement by hand at the point where the script is failing.

Respecting spelling and whitespace

What is whitespace, you ask? It’s all the stuff that looks white on a screen (or black, if you like Dark Mode) but contains invisible characters that the computer does not ignore.

Examples of whitespace:

  • An actual space, as in between words.
  • A tab, like what you use in a word processor. It’s usually 4-5 spaces wide, but it’s distinct from a sequence of spaces. Just ask a Python programmer to explain this to you.
  • An end-of-line character. There are actually several of these, and they differ depending on the operating system. This is one of the reasons why simple .txt files sometimes look insane when they travel from a Windows computer to a Linux or a Mac computer.
  • A truly diabolical example of a whitespace character is a letter that is rendered in a font color that matches the background. Select the line below with your mouse, and you’ll see.

Hahaha! I am whitespace in white color! I got you, sucka!

Why are we talking about whitespace so much? Because Praat does not like spaces. In the olden days, many computers could not handle spaces in file names at all. This is the reason why oldsters such as myself use underscores for readability, as in, sound_and_language_syllabus.pdf. Behind the scenes, spaces in file names have to be modified; in URLs, for example, spaces are replaced with other character sequences. Look at the URL of any website and you will not see spaces in it. This is because computers treat spaces as meaningful breaks between objects.

So, if you open a file in Praat with spaces in the filename, Praat will automatically convert them to underscores in the name of an object. Try it! If you ignore the underscores in your handling of files, which I think many non-programmers tend to do, you will be punished for your carelessness. You’ll wonder why you have what looks like duplicates, or wonder where your file went, or, if you have spaces in the names of your folders, things might not work at all.

Solution: Do not use spaces in file names. Use a concatenation of lower and uppercase letters, as in SoundLangSyllabus.pdf, or, better, use underscores, as above.

Capital vs. Lowercase

Speaking of capitals: capital and lowercase letters are not the same characters to a computer. Whenever a program seems to treat upper- and lowercase as the same, it was explicitly told to do this. So, make sure to respect that difference.

Differences between symbols that look the same to you

Now we get to some really old-school stuff, like the ASCII vs. non-ASCII distinction. The ASCII character set (pronounced “ass key”) is the oldest, designed for English. Even commonly used Western European characters such as <ñ> and <ü> are not part of the basic ASCII set of 127 (see it here, if you need to). The oldest programs do not know how to deal with anything other than ASCII.

And this includes Praat. If you want to annotate a TextGrid, Praat will not let you enter IPA characters in Unicode; you can enter them using deadkey combinations, as explained in the manual, but you cannot paste them in directly from your word processor that uses a proper, modern IPA font.

Where this becomes a problem in working with Praat scripts is if your script depends on labels matching something. For example, if you want to extract all the intervals labeled “g”, but some of your “g” labels are IPA [ɡ], and others are regular font [g]. (Look carefully and you’ll see a difference in those symbols.) For me, some problems I’ve run into involved Russian script ” а” vs ASCII “a”; they look identical but are different to a computer. (There were scam URLs a while back that capitalized on Latin and Cyrillic using some similar looking letters… You think you’re visiting Amazon.com, but really you’re somewhere in the middle of the Azov sea. But I digress.)

Ready to go beyond these basics?

In the confidence builder example, you didn’t change the script text itself, and we did not look at the contents of the scripts. But all the Praat scripts linked above were created by people who weren’t Praat programmers (Boersma and Weenink)–and most can be modified by users such as yourself. You can take these scripts, look at their contents, and change them to suit your needs.

For another confidence builder, then, open the mark_pauses.Praat script as in the instructions above, but before you hit “Run”, do the following: go to “search”, enter “lennes”. That will take you to a line that says

text folder /home/lennes/

Change this line to /home/yourname/, and save the script. Now run it–what do you see in the field at the bottom of the dialog?

What you did is modify the form that the script generates. That window is part of the script, and the field is pre-populated by a default value. All of the form values can be defined either in the form when you run the script or by changing the script itself.

Once you understand that the contents of that file is not magic, you can take on the Praat scripting tutorial in Praat itself, or check out the various resources written by other people.

I like Eleanor Chodroff’s Praat scripting tutorial here. She has some other nice resources on her page.

And now, the obligatory metaphor

If you’ve taken classes with me, you know how I like tortured metaphors. And similes.

The way young people use computers is sort of like Hermione’s magic bag from the Harry Potter and the Deathly Hallows book. It’s a tiny bag, magically crammed with stuff, and she often uses the Accio charm to get things out of it. This is a summoning charm that just find the right thing in the mess–sort of like that search function you rely on. Hermione doesn’t bother to organize books, Muggle clothing, essence of Dittany, and all the rest of the junk in the bag because it’s bound to fall over anyway. And why bother, when you have a magic summoning charm? When you rely on search to find stuff on your computer, or on the internet, it’s pretty much like using the Accio charm.

[Another tortured metaphor: relying on the internet to keep your stuff for you is pretty much Leprechaun gold territory. Internet stuff disappears. You can practice a Zen-like non-attachment to your stuff, or you can keep it locally, and organized, if you want it to be around for years to come.]

To an older person, hearing about this Search approach is akin to learning that you keep your socks and your forks and your toothpaste and your books just randomly piled all over your room, jumbled together. We keep things in separate cabinets and drawers. We know where to find forks not because we have a magic summoning charm, but because we put the forks into the place where forks go.

The way computers actually work in reality is that you have to tell them were the fork drawer is, in explicit detail, without typos. Even when you have an operating system that can search through your files, this becomes useless if you don’t know what to search for. And believe me, a time will come when you won’t remember what you called that one file, or where on the internet you saw that one thing.

Because you see, the search-for-it approach is only good if you know what to search for.

Back to Praat. In setting up an experimental project, there are a few common-sense, fork-drawer-organizing things you should consider doing:

  • Put files into directories. For example, have a “raw_audio” directory where you keep the unsegmented data, and a “segmented_audio” and maybe “textgrids” for the eponymous things.
  • Give files sensible names without spaces. Just ask yourself–would I be able to figure out what all these files are 10 years from now?
  • Keep a small local “readme.txt” file that explains what order you did things in, and what each folder is for, in case you forget (because believe me, you will… it’s not just a matter of how well your brain works but also how much stuff is cluttering your memory; the more you know, the harder it is to recall things, paradoxically).

Okay, I’m done hectoring you for now! Did this help? Do you have any tips to include here, or anything you ran into that I didn’t cover above? Let me know.

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Cyrillic encodings

It seems to be increasingly uncommon for programs to have an easy way to guess encodings correctly and to manipulate them gracefully. Or maybe this is just a Linux problem. In any case, I’ve found myself looking this up repeatedly, after failing to get the right results in various text editors (VIM, Gedit, xed). This used to be so easy in Mac OS’s TextWrangler–there’s an actual menu item, “Reopen using encoding…”, with a drop-down list. You just pecked around the Cyrillic options until you saw something other than alphabet salad.

Anyway, here is the way to view and change encoding. One common source of problems is that the encoding in the file’s metadata is often wrong. For example, Sharoff’s frequency lists are encoded in CP-1251, which he says himself here. But the files claim to be in ISO-8859.

 


$ file lemma_al.txt
lemma_al.txt: ISO-8859 text, with CRLF line terminators

 

This mismatch is what causes VIM and its ilk to display trash instead of Cyrillic. Since the original information is lost, you have to do some guessing. In this case, the following command worked on first try:

$ iconv -f cp1251 -t utf8 lemma_al.txt -o lemma_al_utf8.txt

This converts -f from encoding CP-1251 -t to encoding UTF-8, taking the next argument as the input and the -o argument as the output. Open it in a text editor to see if it did the trick.

Now, CP-1251 is just one encoding. What others might you have to try? There is a good review here. The usual legacy encodings are koi8r, koi8u, cp866, ruscii, cp1251, iso8859. They are known under different names sometimes, so you might have to do some digging to get it right.

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Gouskova 2023

Gouskova, Maria. 2023. Phonological asymmetries between roots and affixes. Wiley Blackwell Companion to Morphology, Eds. Peter Ackema, Sabrina Bendjaballah, Eulàlia Bonet, and Antonio Fábregas. [doi]

This review surveys the phonological asymmetries between roots and non-roots (affixes, clitics). It starts with an extraphonological, structural definition of roots, and considers those non-phonological properties that are phonologically relevant: they are easily borrowed, and they are most deeply embedded. The empirical portion of the review concentrates on templaticism and size restrictions, asymmetries in segmental contrast/inventories, the properties of multi-root words (compounds), and accentual characteristics that differ between roots and affixes. The theoretical section surveys theories that account for these properties: Prosodic Morphology, Positional Faithfulness, the cycle and its analogs, and Anti-Faithfulness. I then critically review several recent and not-so-recent proposals that blur the line between affixes and roots, using the ‘root’ designation diacritically or recasting diacritic distinctions as structural distinctions. The concluding section discusses the role of roots in phonological learnability.

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Gouskova and Bobaljik 2022

Gouskova, Maria and Jonathan David Bobaljik. 2022. The lexical core of a complex functional affix: Russian baby-diminutive -onok. Natural Language and Linguistic Theory 40:4, pp. 1075–1115. [pdf][doi]

Like other syntactic elements, affixes are sometimes said to be heads or modifiers. In Russian, one
suffix,-onok, can be either: as a head, it is a size diminutive denoting baby animals, and as a modifier,
it is an evaluative with a dismissive/affectionate flavor. Various grammatical properties of this suffix
differ between the two uses: gender, declension class, and interaction with suppletive alternations,
both as target and trigger. We explore a reductionist account of these differences: the baby diminutive
comprises a lexical morpheme plus a functional nominalizing head, while the evaluative affix is the
lexical morpheme alone. We contend that our account is superior to two conceivable alternatives:
first, the view that these are homophonous but unrelated affixes, and second, a cartographic alternative,
whereby diminutives attach at different levels in a universal structure.

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Sounds of the World

These are some resources for phonetics students who want to know what languages have certain sounds, how these sounds are produced, and where in the world the languages are spoken.

  • World Atlas of Linguistic Structures: this is a resource on linguistic typology–classification of languages according to various characteristics. There is a page listing features of interest, and the atlas can be searched for specific language names, as well. Here is the page on the velar nasal, for example:

As with any typological resource, it is a good starting point, but you should always look at primary sources for further research.

  • The UCLA Phonetics Vowels and Consonants page: A classic resource that goes with Peter Ladefoged’s books A Course in Phonetics and Vowels and Consonants. For many languages, there are audio files of minimal pairs illustrating unusual contrasts. The audio was often recorded in the field so the quality is sometimes fuzzy. A newer version of the same materials can be accessed on Keith Johnson’s website.
  • International Dialects of English Archive: this has recordings of English speakers reading the same two texts. For American dialects, there are multiple speakers from each state, and their age and some other demographic information is given:

screenshot of dialect archive page

  • Articulatory IPA: A great collection of short MRI, ultrasound, and schematic videos illustrating various sounds.

  • Illustrations of the IPA: From the Cambridge University Press Journal of the International Phonetics Association, a series of articles that do sketches of individual languages’ sound systems. Search the journal contents by language name or sound type. Many of the articles are open source, and they come with audio files of high quality that go with the transcriptions in the book. To see the audio files for an article, click on its “Supplementary Materials” tab.
  • UPSID: the UCLA Phonological Segment Inventory Database. This is one of the older databases, with just 451 languages, but it is supposed to be balanced geographically and genetically (that is, related languages are not overrepresented). It’s a good starting point for researching the typology of sound inventories.
  • Interactive Sagittal Section: Pose the vocal tract in your browser to see which sounds are produced.

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PhoNE workshops

PhoNE (Phonology in the NorthEast) is the current incarnation of a series of annual workshops, mostly on phonology, which have been meeting on the East Coast for over two decades.

Historically, the names were acronyms based on the participating schools:

RUMMIT was the Rutgers-UMass-MIT phase of the meeting. This name was used from 2009 until 2014 or so.
UMMM was the UMass-MIT Meeting on phonology, a.k.a. MUMM. These names were used 2008-9.
HUMDRUM stood for “Hopkins, U of Maryland, Rutgers, Umass”. This name was used in 2000-2009.
RUMJCLaM was the “Rutgers-UMass Joint Class Meeting”. Before that, RUMD. These names were used in the 1990’s.

Here are the locations and dates of previous meetings.

2024: UMass
2020: NYU (Cancelled due to Covid)
2019: Yale, April 13
2018: MIT, March 31
2017: UMass, April 8
2016: NYU, April 9
2015: Yale, April 2
2014: MIT, April 26
2013: UMass, April 6
2011: Rutgers, May 16
2010: MIT, December 4
2009: UMass, November 1
2009: MIT, May 9
2008: UMass, November 22
2008: MIT, March 29
2008: Rutgers, April 26
2006: Hopkins
2006: MIT
2005: UMass
2004: Rutgers
2002: UMass
2001: Hopkins
2000: Rutgers
1999: Rutgers
1998: UMass (RUMJClaM)
1997: MIT (as Bay and Berkshires Phonology)

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Features in phonology

This is a 30-page overview of phonological features, which I wrote for the phonology classes I teach at NYU. It is intended to be accessible to both undergraduates and graduates; I usually ask the undergrads to read sections 1-4 and 9, and the grads to read the whole thing. If you would like to cite this review in your work, refer to it as follows:

Gouskova, Maria. 2016. Features in Phonology. [pdf] Ms., New York University.

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