The Nanogenmo project of my choosing uses RNN based models(LSTM) and has corpus cut-ups from dataset Wolff and Friends. The result shows different text from the written and verbal output. I wasn’t able to figure out how to generate 50,000 text using this model at first, but I later asked for help and basically made a malware that generates continuously, which broke my memory and froze my computer tons of times. The voice p5 output uses the two different datasets which is interesting, so the speech narrates the entire story differently.

Example of input: hello

Example of written output:

hellopped in the little cups and the lighthouse faced by the pillows of the streetthe young man with a little shop in the night to the dining-room with the dollar, which was cold in the street at charleston to the station and crawled up and down beneath the horizon. it was not the shock of the superior of the sheet that had been so much to be done by his kindness. the ancient scribbler had a shot with the stream of the streets, and at last we had a different scrap of real people who began to help the long grasses, the sky changed in a rider the other day at the seat of politics with a little mottled coat of his fingers. it was a great deal of feeling of the brain. the language was a profession, or in the end the conference and the laboured gentleman leaving the first example of the man who could see her characteristics of the string of the mother with a good deal of silence. he had a constant servant girl wet on the terrace with a strip of laughter in the garden, and at the same time she

: No was a pretending to get off and go to the way to the wrong to me to be the most a lot of the table. Ross is not the other thing as some bad, and they’re not having a great time close and the either person. And when that was the beautiful boy because we were at the tounger of the book for a stupid puts away. (They kiss back to the phone and starts to give a bad is gonna be a lot of card out of the couch.] Dr. Green: I don’t know what the half. (They lose the whole beach other.) Rachel: Oh nopped in the little cups and the lighthouse faced by the pillows of the street The young man with a little shop in the night to the dining-room with the dollar, which was cold in the street at Charleston to the station and crawled up and down beneath the horizon. It was not the shock of the superior of the sheet that had been so much to be done by his kindness. The ancient scribbler had a shot with the stream of the streets, and at last we had a different scrap of real people who began to help the plate Joey with him and starts to bring the phone.] Chandler: Oh yeah. Are you sure you’ve got so scared before he just comes down! Chandler: I don’t know what you go here and started at her. He didn’t be pretty cookies. I mean I just think we can do this off the baby to the camera in the bathroom. Rachel: Yes, he can’t be about the wedding. Ross: No-no-no-no, I think they were the baby to tell you to must see the light thing, I was so so so should be the table and I had to be a little chef. he long grasses, the sky changed in a rider the other day at the seat of politics with a little mottled coat of his fingers. It was a great deal of feeling of the brain. The language was a profession, or in the end the conference and the laboured gentleman leaving the first example of the man who could see her characteristics of the string of the mother with a good deal of silence. He had a constant servant girl wet on the terrace with a strip of laughter in the garden, and at the same time she wants to get it out and the time, he gets the money through the ball of her show and the dress on the bathroom.] Phoebe: Hey! (He starts to leave and stops to him in front of the bedroom) Oh my God! What does it is it. Rachel: Yeah, what is this more in the ball and started and he has to be a second at the money for a problem, or really weird everything when you guys feel better we are not a good cheese? Ross: Who are you doing? Joey: (singing) No, no, I know what you want a job! Chandler: I dondid it, and was not only in the second part, and to think he had been for ever in the nineteenth century. It was not that the life of it must be made of the season which she had seen through the broad and contemptuous convenience of his own way. He had stood there at Latin station and looking at him in her chair and see that the maid had not stirred her as if he were in the army of the last words. He was on the top of the drive by the sea. Never did the story at Paris and the barrel organ……

Below is the interface:

I emailed Yining to help figure how to generate the 50,000 text written form for the output. But instead, I found it impossible so instead I used this code:

function gotData(err, result) {
// Update the status log
select(‘#status’).html(‘Ready!’);
//select(‘#result’).html(txt + result.sample);
select(‘#original’).html(txt);
myText += result.sample;
select(‘#result’).html(myText);
textInput = select(‘#textInput’);
textInput.value(txt + result.sample);
foo.speak(result.sample);

Until I spoke with Dan Oved who thought of a way to continuously generate it with the last sentence of what is input (more dynamic) but it broke my computer a few times.

What is a “novel,” anyway? What techniques exist to maintain narrative coherence over a sentence, a paragraph, a chapter, a collection of chapters, etc.?

A novel is a relatively long work of narrative fiction, normally written in prose form, and which is typically published as a book.

The file can be found below. Unfortunately I didn’t save the code before I made it into the final project:

I was told I was make a branch and revert the history so it can go back to nanogenmo malware which generates 50k words. Github: https://github.com/sl7211/Interoception

The drive has a copy of the older version, not sure if it auto-generates.

https://drive.google.com/drive/folders/1-_WO2QEwqtjuzYNbm1Zf7hEJE5wnwkFC?usp=sharing

NYU 2018–2020