procedural name generator


For example, carrie and kerry have the same pronunciation K EH R IY, so if I wanted to modify the pronunciation to K EH R IY AE N, Id only get a single output, kariann. copyright Unity AssetStore Price down information All Rights Reserved. If the word is too short, we override the requested number of syllables to add more. Would a rose really smell as sweet if it was called dungy binjuice? Eventually, the program generates and stores all possible words. * From April 1, 2021, Japanese law "mandatory total amount display", Please use the link below for tax-excluded display, [ PUBLISHER SPOTLIGHT ] From 8:00 on July 12, 2022 to 23:59:59 on July 25 (PDT), until finish Maybe some civilization in your game writes the AH sound as ' and the L sound as ll and we want Michael to be written Mich'll. In 2018 I played more with alignment in a project to procedurally modify spelling, and I made an interactive demo where you can put in your own words. However, I also wrote an ARPAbet to Apple converter arpabet-to-apple.py so that I could use Apples speech synthesis to hear some of the new words I was generating. The generator maintains models that look up to "n" characters back, where "n" is the "Order" option value in the settings section. To get around this restriction and make sure 'Meu' and 'ZoBuGaGaZoZo' can still be included, let's make the minimum syllables 1, the max 6. Hence I arbitrarily decide I want them to be between 3 and 12 characters long. propane coleman generators generator 18kw 'MeuGa' For the procedural name generation I wanted to try sequence to sequence[15] models {1}[16]. word = word + random.choice( syllables ) What about adding several syllables to a word? When we need a new name, we generate it and check it against the set. The aim of our name generator is to help you find the perfect name for any occasion. This means they need to store everything in memory. This seems like a potentially useful way to procedurally generate names that are similar to existing names, but spelled or pronounced differently. Allison also uses the CMU dictionary and has built a Python library[22] that handles both pronunciation (lettersphonemes) and spelling (phonemesletters) using sequence-to-sequence neural networks. This library is much easier to use than what I did, and it makes me want to try playing with this topic again. Press the "Generate" button to begin, or select "Settings" to configure advanced options. You signed in with another tab or window. Ok, not the right answer, but an understandable mistake.

Thats ok in this case, as my goal was to learn something about neural networks. 'BuMeuZo'. Fortunately its actually making checkpoints along the way. We'll then check the length of the word as we generate it. 'MeuZoZo'. You can get compute resources: Azure, Amazon EC2, and Google Compute Engine give you easy access to lots of computing power (including GPUs). Thats one million times as much computing power. I took 5000 names from the U.S. Baby Name list[36], changed a few phonemes at a time, and asked for the spellings of the new names. [Update <2020-05-21 Thu>: Allison Parishs video[21] is worth a watch!

We didn't invent it, it's the same system used by Blizzard for their battletags. The combination prefix + suffix means we can automatically generate around 20 million unique names. The Shadoks are aliens that look a little like birds. M AY K AH L produces michel. Now, I can get 50 teraFLOPs for $10/hour. I read about convolutional[4] neural networks {1}[5] - {2}[6] - {3}[7] - {4}[8], which are about grouping inputs together, primarily for image processing, but also can be used for text processing. I usually need a mini project to learn a topic, so I decided Id use procedural name generation to guide my learning. They don't have much memory so their language is made of only four syllables: 'Ga', 'Bu', 'Zo' and 'Meu'. If we ever need to generate more words, we can easily add a syllable to the syllables list (conveniently, the. Based on that data, you can find the most popular open-source packages, But it's not just people who need to be named. Whether you like it or not, people do make snap judgements and form first impressions. Select one of them, click in space and see what happens! Names matter. - Template included to help you get started and create your own dictionaries in minutes. All the other words will also have a lot more 'Meu' syllables included: 'MeuBuGaMeuMeu' The neural network outputs meckle and mookle. I also wanted the players' default name to be amusing yet neutral to encourage people to personalise their name. I dont know. However I dont know what Id actually want from a name generator like this, and I dont think Id use neural networks for it. There are dozens of training presets, and the corpus can be manually edited through the "Settings" dropdown section above. The neural network may be good at capturing English spelling rules for existing words, but I think alignment would offer more possibilities for the designer or procedural generator to control how generated names work. We cap the number of attempts at an arbitrary 99. Download Avoyd. We'll also introduce an arbitrary boundary to how many attempts we make. I then tried using the model: I typed in names like michael and got back pronunciations like M IH CH EY L (pronouncing the ch like cheese and not like kite). Lexic is an extensible, customizable, procedural name generator. To use the generator as part of a registration system, you will need to store the list of unique generated words / usernames in a permanent repository, for instance a table in a database. What if we wanted to increase the chances of specific syllables appearing more often than others in the final word? This number will be the number of syllables in the word we'll generate. We'll call it num_syllables. I let it run for 6 hours, and it produced much better results. The "Similar To" parameter allows you to sort the generated names by their similarity to the name that you enter. Spit out lyrics from the song Mad World by Tears for Fears. hours Yes! It demonstrates the markov-namegen haxelib.

The name generator was written using Haxe. I stopped it after half an hour. Filter results by length, start, end, content and regex match. Presets include funny names, fantasy names, Scottish names, German names, Irish names, names of towns, animal names, theological names, werewolf names etc. The "Start", "End", "Includes", "Excludes" and "Regex" options are used to filter the generated words. There isnt one right way. not use the computer as a space-heater). 'Meu' - 1 syllable - 3 characters - ok lengthwise We're currently developing a cool app based on our site. This is called alignment: There are a bunch of techniques for alignment. 'MeuGaZoGaMeu' So instead I read the g2p-seq2seq code and modified it to work on phonemes to graphemes (phoneme2grapheme.py). A great side-effect of writing this detailed tutorial is that I found out my Shadok name generator didn't work properly and I could also simplify it. I had hoped to use the Web Speech API but it seems pretty limited at this point. 'BuZoGaBu' If you want to go further, in the Voxel Editor open 'Tools' > 'Edit Tool'. You can get code: tools (that all seem to start with T) include Torch, Theano, TensorFlow. Hundreds of customizable/combinable training data presets. Now let's make them more interesting by varying the number of syllables in each word, say between one and five. Ask HN: Hows your experience building collaboration tools (like Figma)? Before we continue let's undo this change and go back to equal probability for all syllables. Hence as an example, retrieving the value stored at index 2 in the syllables array returns 'Zo': To pick a syllable at random, all we have to do is generate a random number between 0 and 3, and use it as the index from the syllables array: Now all we have to do is add the syllable at the end of the word: Writing this in one line by nesting the commands we get: This adds one random syllable to the word. We're now able to generate around 2000 different Shadok words of varying lengths. 'GaBuZoMeu'. I used the TensorFlow example for city name generation and ran it on the U.S. baby name list[14]. It's an animated series that first aired on French television 50 years ago. I started this mini-project primarily to play with neural networks. Neural networks are neat, and there are more ways to use them than I had known about before. I later found this program[29] to convert formats, but didnt try it because I had already written my own. Its not that different from Markov chain name generation. Similarly random names can be used to effectively test features such as form fields an newsletter sign-ups. Search at random or filter and sort by gender, popularity, birth year, country, personality and many other interesting properties. 'BuBuGa' We've just seen we could make long and short words by randomising the number of syllables they're made of. This is the method I've used for generating default usernames in our enkiWS system (simplified, I'll explain the other trick I used further down). If I wanted separate carrie carrianne and kerry kerrianne spellings itd be helpful if the neural network gave me a list of possible spellings, and then I could pick one closer to the original spelling. Thanks to the suffix, we can have several people using the same prefix: Ada#9087 and Ada#2766 can safely coexist. The neural network outputs feichel and vical.

'BuMeuGaMeuGa' It also means we can allow more short, 3 letter prefixes.

Leaving procedural generation aside for a moment to improve the algorithm: we can calculate the number of syllables from our list of syllables and the desired word lengths (so we can easily change our requirements for the length of words or use a different set of syllables.) as well as similar and alternative projects. (Note: I didnt actually use the results of this step; I only did it to make sure I could run it, before changing the code.). As cool as neural networks are, theyre still a black box that doesnt offer me a lot of control over the output. 'BuGaMeu' You can specify male names, female names or both. Random fake data generator for test and development purposes. Its not using the pronunciation at all; its just predicting what letters fit together. Configurable corpus, order and prior model parameter settings. We could program clever things to avoid this situation, but let's be pragmatic. But the more we use it, the more the set fills up and the harder the program has to work randomly generating words that are not already in the set. It acts like an additive smoothing factor, making the generated name content a bit more "random". Run these on Mac: Note that the [[inpt PHON]] syntax doesnt work with the voices added in newer version of Mac OS, according to this stackexchange question[30]. It turns out the emphasis annotations I had removed to keep things simple actually make a big difference in pronunciation. For michael M AY K AH L what happens if I change the initial M sound to F AY K AH L or V AY K AH L? Auto generates random file and folder names that look perfectly natural. 'BuBu' First I'll explain how it's built, then the features I added to it to make sure the names are within an arbitrary size range, and more importantly, unique. minutes These are recurrent neural networks but they wait until the end of the input string before writing out the output. We enjoy watching you read your creations on YouTube. GaBu#2365 The generator generates as many names as possible, then filters and sorts the results according to tweakable criteria in the settings section. Press "Generate" to begin, "Random" for a random theme, and "Settings" to customize. Our first generator, Song Lyrics Generator was launched in 2002 as a student magazine project. when you set your display name you'll see the Shadok name generated for you (the suffix isn't displayed). 'GaMeuBuMeu' The noUiSlider settings sliders are WTFPL. Otherwise, if it's already in the set, we discard it and repeat the process until we find a name that's not already in the set. days This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. - Works out of the box, no setup, no configuration required, just add to the scene and start using with a single line of code. With 'Ga', 'Bu', 'Zo' and 'Meu', we can create many combinations resulting in words. 'Zo' fills a structure with randomized data to mock a service or other model provider. 'MeuBuGaMeuMeu' - 5 syllables - 13 characters - too long. It turns out the CMU Sphinx project has already implemented translation from graphemes to phonemes, using for training the CMU Pronouncing Dictionary[18], which has an ascii (not IPA) representation of pronunciations for over 100,000 English words. Note - in python, instead of random.randint() you can use random.choice() to the same effect: An easy to use race-based fantasy name generator. A couple of years ago I wrote a simple procedural username generator in the Shadok language for our players registration system (more about 'Les Shadoks' below) for fun. but we count each attempt we've made at generating a unique word. For instance I want to generate player names and I want them to be neither too short, nor too long. If it risks becoming too long we stop adding any. This algorithm (it's a recursion by the way) works very nicely when the set is empty or almost empty. 'GaZoBuGaGaZo' With alignment, we can not only change the m to z without affecting the rest of the word, but we can also change how some sounds are spelled. Instead, I started with the technology in search of a problem. For spelling I looked for projects that convert phonemes to graphemes but I didnt find anything. Names typically follow a different structure to typical placeholder text and are therefore randomly generated names look more natural to clients than Greek or Latin. Great! With pronunciation there are several projects that do what I want, including some using neural networks. I downloaded their g2p-seq2seq code[19]. TensorFlow has an example program to translate English into French. This generator is suitable for generating all sorts of names.