How to start a manuscript (and finish it at some point)

Publish or Perish” is a common saying among scientists. But in order to publish, we must,  after the experiments have been performed and the analysis done, write. Of course I enjoy writing, but it is extremely hard and painful. Literally painful. Not only it is very hard to come into the writing zone. Staying there is even harder when you stare at an empty page. This is the time when I procrastinate most: I check emails, repeate analyses, improve the format of plots, watch ted talks. You probably know what I’m talking about.

The hardest job, at least in my experience, is to start a manuscript — the first attempt to put down the first thousands words forming a concise text. Over the years I came to realize that there is no such thing as a perfect first draft. Neither a second. Furthermore, I came up with several techniques in order to overcome the first painful hours with filling pages. Here, I would like to share some of my insights with you. The techniques are based on the idea to focus on one problem at one time. Some of these things seem to be very obvious, but believe me, repetition is the key to proficiency.

The baseline of a successfull writing start is preparation

Whatever you are doing, writing a term paper or a journal paper, you are presenting knowledge for a reader. Before you put any words to paper (or your screen) and formulate sentences, you need to know what you are talking about. Whenever you want to start writing but have only vague ideas about what to write, you will fail.That is the simple truth. Depending on what part of your paper you want to write, you need to prepare differently.

For an introduction, you need to do the research on your topic, find papers, read them, skim through the results and discussion in order to  not only report the background of your paper but also formulate precise hypotheses.

For a results section, you need to have the results of your analysis (be it analytical, statistical, or whatever).

For a discussion, you need to have a results section, otherwise there is nothing to discuss. Also, start working on the discussion only when you have finished the text on the introduction and the results.

Technique 1: Keywords

Never, I repeat, never start a new text by trying to write correctly formulated sentences. Embarking on a writing journey with correctly formulated sentences is the road to procrastination and frustration.
Do you remember what the aim of a paper is? Right, to provide knowledge to your reader. However, when you start writing a paper by trying to formulate complete sentences, you shift the focus of your task from transferring knowledge to finding the appropriate words and syntactic structure. Do not waste your energy on such a thing. Start with writing down your knowledge in the form of keywords. The keywords need to convey most of your knowledge, but it is not be important which exact words you use. Again, how you perform this task depends on the section you are writing.

Write a keyword-based summary of the papers you read. Provide a short phrase for each of the topics: Who has done it, what was the point, what was the method (experiment, analysis, etc.), what was the finding, and what was the interpretation? Write down your hypotheses.

Start putting keywords down about your analysis. If you have a figure, describe the figure. If you have a summary table for a regression (ANOVA, ANCOVA, LMER, GAMM, BAYES, etc.), describe your effects using general language (e.g. “In level A, Y was slower than in level B”, “An increase in Y was associated with an increase in X”). Do not waste your time and your energy with exact numbers. This is the first draft. You need to regard your first draft as the placeholder for exact numbers, precise formulations, and sparkling-from-intelligence metaphors.

You have probably guessed it already: Start with keywords. Reread your introduction and results and write keywords about your main findings. Write keywords about how they are in line or differ from the literature you consulted. Write keywords about how you interpret your results. Write keywords about the problems you encountered.

Technique 2: Talk to an audience

The next step seems easy: take all these keywords and formulate sentences out of them. However, this is still hard to do, to take all those unconnected and sometimes contradictory pieces of knowledge and bind them together into a coherent and readable text. When you begin to write right from the start, you might end up struggling with correct formulations, nice words and nice syntactic structures, instead of doing what needs to be done: Formulate a text. Now, I came up with two possibilities in how to circumvent this struggle.
The first possibility is to tell the things you want to write to a friend. Tell him or her about your problem, what you have done and what results you found. The second possibility is to dictate and record  this onto a recording device. Or even better, do both. If you don’t have anyone at hand or don’t want to bore your friends with your scientific ideas, take your recording device and go on a walk (we need to do that more often, anyways).
Here is what happens when you start talking: Instead of struggling to find cool sounding words and sentences, your brain will put all the effort it takes to create a coherent and understandable version of what you want to say so that your audience understands your message. Humans communicate, humans try to put sense into their messages. Use that power.
Once you have recorded your text, transcribe it (e.g. using transcription software such as F4). And voilà, you have your text. You will be surprised, how much you have to talk about your topic all of a sudden. Furthermore, during transcription, you start to think whether what you said actually makes sense. However, do not rewrite your transcription. Literally put down every word you have spoken.

Technique 3: Rewrite

Now you have something to work on. Now, once you have a text with complete sentences, you can start to invest your effort into cool words and nice sentences. You do not need to focus on remembering the knowledge you want to include into your paper; you do not need to focus on performing an analysis; rather, you can focus and invest your all of your mental energy on correcting your text. And the surprising thing is: correcting and rewriting is a lot easier than writing down new sentences.
This is the time where you start including precise information about your analysis, i.e. exact numbers such as slopes, t- and p-values, and everything which is connected to your analysis. This is also the time when you can redo your research about questions which came up during the first draft.

Technique 4: Write regularly

OK, this is not my technique. It is from “How to write a lot” by Paul Silvia. He suggests, and I can only recommend this, to make room for writing every day. At least one our. It is not important whether you do this after waking up, or before going to bed. But save one hour (or two if you are in the mood) only for writing. Turn of your mobile phone, your internet connection, shut your door, turn off your TV,  and start to write. Silvia shows data that this is the only technique by which you can make progress. If you wait for the muse to kiss you, you can keep on waiting forever. You need to sit down and write. Every day!

Technique 5: Perform different tasks at different places

Sometime I heard that Walt Disney used three different rooms for his work – one room for the coming ip with ideas, one room for writing and one room for drawing. Whether this story is true or not, it makes perfect sense to adapt this technique for writing papers.
A short excursion: Think about your getting up habits? What is the order of going to the bathroom, making coffee (or tee), brushing your teeth, etc. Probably it is the same every day. And try to recall how unhappy you are, when this order is broken. The reason for this is that we have habits how things have to happen. Make it habit to write every day! Make it a habit to think about problems in one place (e.g. in the shower, on your way home, on your bike, while exercising), to write down keywords in another place (e.g. in the library, the pub, the cool coffee house next door), to rewrite in your office (or at home, if you cannot work in the office).
Furthermore, get habits for starting to write. For example, I always drink a cup of coffee before I start to write. It works like a mental switch.
Make it a habit to plan what you want to do in your writing hour. For example: Write 1000 words. Rewrite one chapter.
Make it a habit to reward yourself for work you have done. Not only, it makes you happy having done the work you planned. No, it makes you happy that you (finally) can watch the YouTube video you were eager to see. Rewarding yourself keeps you from procrastinating, as you change your habit from watching YouTube for procrastination to watching YouTube for reward.

Technique 6: Take your time

Rome was not built in one day. Neither is written a scientific paper. Take your time. After having written your first and second draft, leave the manuscript alone for a couple of days (sometimes even a week or two). Work on other things. In this way you clear your head from the current project, allowing oyu to reread your manuscript more critically, to find errors in the writing, the structure and the argumentation. Do this at least twice before you pass your manuscript on to someone else.

Good writing!

English Orthography – The capitalization of nouns between the 17th and 18th century

I recently visited the “39. Jahrestagung der Deutschen Gesellschaft für Sprache” (DGFS) in Saarbrücken, of which I am officially a new member (Yeah, it was about time!). The weather was terrible, it was pouring during my entire visit. Less time to procrastinate and walk through Saarbrücken, more time to listen to interesting talks. And there were plenty of them.

One talk, namely the one by Stefania Degaetano-Ortlieb’s on discourse connectors in scientific writing, inspired me to write this post. It was interesting, indeed, but I thought, connectors, schmectors, what is with the nouns of that scientific texts from the early 18th century. Almost all of them were written with an uppercase beginning letter.

I couldn’t believe it. Uppercase in English? It is like German or… actually, it seems that this is a very German pecularity. Nouns in Danish and Norwegian have used to be written in uppercase. But the practice was abolished in 1869 in Norway and in 1948 in Denmark. Remains Germany, the only country in the world expecting its kids to know and understand the difference between nouns and all of the rest of word classes. How dare they…

Back to English. I went to google ‘sNgram Viewer. The website is amazing and allows you to inspect word frequencies across time on the basis of modern and historic texts. I checked the spelling of one of the most common words: house starting at 1500 and ending in 2000. Check out what I found in the following figure. The red line represents “house” with lowercase, the blue line “House” with uppercase.

Red line: house. Blue line: House

There is a clear dip in the time from roughly 1650 to 1750,  where “house” in lowercase is in the minority and “House” in uppercase is in the majority. Before and after that periode the lowercase spelling is in the majority.


Ok, that was intriguing, so I checked six of the most common nouns in almost every language: “House, Houses, Man, Woman, Child, Children” in upper and lower case. The following figure shows you the ratio between uppercase and lowercase spellings with values above 100% indicating that uppercase spelling is in the majority.
(if you want to test it on your own, the formula was: (House+Houses+Man+Woman+Child+Children) / (house+houses+man+woman+child+children))

Ratio of uppercase to lowercase spellings. Above 100% represents uppercase in the majority.

This supported my assumption that in the one hundred years betwen 1650 and 1750 something in the English writing world happened. The phenomenon happened in both, American English (left) and British English (right).

Well, that said, I had to find out what actually happened. I started with an entry on wikipedia, which was more than boring. It stated only the contemporary capitalization rules. Nothing historic. Then I googled the topic. I found roughly four million entries. Checking out the top 20, I found that none were conclusive. There exist some theories. For example, one states that the script written at that time did not allow a proper distinction between words written in uppercase, because the letters were easily confused. As a result capitalization was abolished. But that was not very rewarding, because I still urged for knowing: WHY!? Why did capitalization start and why did it end?

Most German students think, capitalization is a mean thing teachers made up to torture them. However, studies in reading show that a reader seems to benefit from capitalization as comprehension is facilitated due to the additional “cue”  (read e.g. here). But if that was really the case, I wonder why only German sticks to capitalization of nouns and all other alphabethic based orthographies don’t use it.

On google scholar I found Richard Venezky’s Book “The American way of spelling“.  Unfortunately, the entire chapter on the writing system itself was not available on google books. The library of my university does not have it in stock. I thus decided to contact Dr. Venezky, just to be informed by the email deamon that his email was not valid anymore.

I ordered the book from another library. I will hopefully find something in a couple of weeks. And if not… well, I doubt that I will work myself through historic texts on spelling.

Can we see speech?

Of course we can! But let us start somewhere at the beginning!
Remember the scene in 2001: A Space Odyssey in which the two characters Dave Bowman and Frank Poole conspire against HAL 2000, the omnipotent AI of the Discovery One. They isolate themselves in a shuttle, assuming that since HAL cannot hear them anymore and they can talk freely. Well, they obviously forgot HAL’s ability to read lips.


Naively, we know that we can read lips and map their movements somehow onto something like a “meaning”. It is said that deaf people use this technique. This means that our brains not only contains an articulatory representation of speech, meaning how we need to move our lips and tongue and jaw in order to speak. Also, we have a representation of how our mouth looks like when we speak. You can easily check this on your own: Next time you watch a movie in a foreign language, count how often you deliberately watch at the character’s lips in order to enhance perception!

In the 1970, Harry McGurk and his research assistant John MacDonald were able to show  what has now become known as the McGurk effect: When you mismatch visual and auditory information for a syllable, e.g. [ba], makes you hear something completely different. Check out the following video:

What happens in the movie above is the following: You see the mouth movement of the [ga] syllables and hear the auditory signal for [ba]. Your brain tries to resolve this conflicting information and what you  hear (or are supposed to do so) is {da}. If this is the case for you, then this effect clearly shows that the brain stores both, the visual and the auditory information, and uses it to process speech. If this was not the case, you would not have a conflict and perceive something completely different.

Massaro and Stork (1998) “Speech Recognition and Sensory Integration” explain this effect on the basis of cue similarity, with cues being pieces of information in the signal that the brain processes. [ba] and [da] share auditory cues, [ga] and [da] share visual cues. When you mix these, i.e. auditory [ba] + visual [ga], the brain choses that output, or perception, which matches a category with the highest probability. In case of the McGurk Effect: {da}. Massaro and Stork used this probability and similarity based algorithm to create a computer program which can read lips – the precursor to HAL. Simultaneously, the McGurk effect shows us that the brain stores and uses all provided physical information which is contained in the input.

Therefore: Yes, we can see speech. It is nothing special, quite the contrary. The information is there and the brain uses it!

Together with my colleague Daniel Duran from the Institut für Maschinelle Verarbeitung, Stuttgart, we investigate in a modeling project, how cue overlap and frequency differences between [ba], [da] and [ga] might be a source for the McGurk Effect. We want to investigate this by comparing  the “Naive Discriminative Learner“, an algorithm capturing human and animal learning behavior, and “Exemplar Model”, a model that captures the creation of phonemic categories on the basis of similarities.

We presented our preliminary results during the second Workshop at Schloss Dagstuhl in our talk “Modelling multimodal integration – The case of the McGurk Effect”. This time, the workshop was attended by Bernd Möbius, Laurence White, Frank Zimmerer, Uwe Reichel, Ingmar Steiner, James Kirby, Antje Schweitzer, Katrin Schweitzer, Mike Walsh and our invited guest, Janet Pierrehumbert. The results are promising, and also to a certain extent surprising.



Phonetics goes Rocket Science

Last semester, I wanted to show my students the turbulences in the air around the mouth during articulation. Unfortunately, I was not able to find any video material which could nicely illustrate such effects. We therefore started a cooperation with the “Deutsches Zentrum für Luft und Raumfahrt” in Lampoldshausen. Together with Friedolin Strauss from the DLR, Denis Arnold, Tino Sering and myself, we recorded a total of 45 seconds of speech using a schlieren photography captured by a high speed camera.


You might be wondering: “Why only 45 seconds of speech?” Well, the camera recorded with a sampling rate of 10 000 frames per second. After recording roughly 5 seconds of speech, the system had to upload the data (20-30Gb) to the server. This took around 30 Minutes. In total, we spend four hours of recording and, as you can see, shooting nice pictures.



Schlieren photography allows you to track changes in the density changes of a medium, in our case of the air. With a temporal resolution of 100 microseconds (0.1 milliseconds), the camera allows us to investigate subtle changes in the airflow out of the mouth and out of the nose. We saw effects we have not anticipated before already in the screening of the material. We are looking forward to the analysis, once the data will be on our servers.

If you want to know more about our visit to Lampoldshausen, the DLR published a blog post here (in German).

Introduction to R – rewritten

I completely rewrote my Introduction to R. The premise of the new manuscript is that you want to processes a written or spoken linguistic corpus using R in order to perform statistical analyses.

I reused lots of text of the previous script, especially the static introductions about what works how. But now it is embedded into a narrative: “preprocess a corpus”. The idea is to teach you all the necessary stuff only when it becomes necessary.

You can download the current version here.

Phonetik und Phonologie im deutschsprachigen Raum 2016

Last week I visited the PundP in Munich. Felicitas Kleber and Christoph Draxler did a wonderful job organizing this beautiful conference. The great thing about PundP is that it addresses not only phoneticians and phonologists who have been working in the field for a while, but also undergraduate students and PhD-students. It provides a friendly environment where one can find constructive criticism and great inspiration for one’s work.

I met wonderful friends there, among them Daniel Duran, who presented his revolutionary learning-and-testing environment; Adrian Leemann, who presented on his App “Dialäkt Äpp”, Cornelia Heyde, who studies the articulation of stutterers by means of ultra-sound and Mathias Scharinger, who is investigating neural mechanisms of perception.

This year, I myself presented the Karl-Eberhards-Corpus of spontaneously spoken southern German, work which I have been doing together with Denis Arnold for the last three years. The corpus consists of one hour conversations between two friends. It is annotated and corrected at the word level. Segment annotations are provided on a forced aligner basis.

Left: myself; right: Daniel Duran

Text to speech on your phone

There is plenty of stuff like books and articles I would like to read but simply don’t have the time.  On the other hand, I use the car to drive to work thinking: What a waste of time.
I found a solution:  a text-to-speech system for the smart phone called “@voice aloud reader“.

It is capable to process PDF files, text files, doc files and much more. It refers to the text-to-speech system already installed on your phone but you can install many more voices as well as languages.


Three and a half years ago I started working at the Department of Quantitative Linguistics, University of Tübingen. My new field of research was articulography, a method to monitor and record the movement of the tongue and lips during speech production.

Together with my colleagues Denis Arnold and Martijn Wieling, we made a movie to advertise for our experiments. Recently, I found the movie again on youtube:

Word counts and phonetic counts

More and more phoneticians, as I do,  rely on measures of experience, such as frequency of occurrences, in their investigations. I have been struggling with these for the last three years and ended up with a fairly easy accessible data base of frequencies for word forms and phones and biphones (phonotactic frequencies) for German.  It is based on CELEX and the SDEWAC corpus.

The database can be accessed here and a description here. How to cite the database is included in the description. Thanks for sharing and citing.