Technology behind AI writing assistants

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The first AI writing tool dates back to Stanford’s spell checking software in the 1970s. AI typing assistants have come a long way since then. Today, online writing tools use AI, predictive analytics, and NLP to generate new ideas, check tone of voice, and structure stories. Additionally, the rise of GPT-3 has further revolutionized the content ecosystem.

Amy Cuevas Schroeder, Content Director at Writer, talked about how specialists use AI to make writing engaging and in tune with the brand voice. According to her, grammar models can be trained on a huge data set of well-edited content, and deep learning will allow the model to grasp the fundamentals of syntax without prescribed or rule-based training.

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In this article, we’ll look at how AI writing assistants work and list some of the best writing software out there.

Grammar and writer

Building and deploying grammatical error correction models (GEC) based on data, not rules, has gotten a lot easier with advances in AI. Many tools are still based on open source grammatical error rule sets. That is, thousands upon thousands of the most common mistakes writers make. Writer has created proprietary training and assessment datasets based on native speakers and professional writers.

Grammarly uses NLP to fix spelling, punctuation, grammar, and word choice errors. His GEC system picks up an incorrect sentence and outputs a corrected version. Therefore, GEC is treated as a translation problem where incorrect sentences are the source language and correct sentences are the target language.

Grammar error correction

Transformer models search vast amounts of text to refine linguistics into statistical patterns. In addition, transformers are able to generalize and make local decisions for greater accuracy.

For example, suppose the model needs to fill in the blank for the phrase ‘the cat sat on the ____’. The model doesn’t need to know the meanings to find a suitable word – it examines the data and statistical patterns to conclude that the best match would be the word “mat” rather than “Roomba”.

However, because transformers are not mature enough, the best performance is usually obtained with a hybrid approach, e.g. B. by combining different methods such as tailor-made rules, deep neural networks and language models.

A comparison of Transformer language models (BERT, GPT-1 and GPT-2) with two current similar systems on standard GEC datasets.

Source: Grammarly Engineering Blog

Mark approach, don’t write

Grammarly combines NMT and seq2seq to create a custom translation that highlights the phrase to be corrected. This reduces the task to a language comprehension problem that allows researchers to parallelize the inference and run it faster, thereby simplifying training.

The model consists of 5,000 transformation tags that cover some common errors, such as: B. Spelling, number of nouns, subject-verb agreement and verb form. The vocabulary covers 98 percent of the errors that are present in the CoNLL-2014 (test) for evaluating the model.

The GEC sequence tagging model is called GECToR- and is compared with Google’s BERT due to its encoder layer consisting of a pre-trained transformer with two linear layers and Softmax layers on top. These are responsible for error detection and token tagging. The model is trained in three stages:

  1. Implementation of a synthetic data set with 9 million target sentence pairs with errors.
  2. Fine-tune the model on real data sets consisting of 500,000 sets.
  3. Fine-tune the model on real data sets consisting of 34,000 sets.

Research showed that the model predicted the tag-encoded transformations for each token in the input sequence that were further used to modify the output sequence.

Source: Grammarly Engineering Blog

Top AI writing assistants

Content creation

AI Writer – AI Writer uses its auto-write and text generation capabilities to generate new content for users to create error-free, information-dense content based on the user’s heading.

Acrolinx – Acrolinx helps create content that is driven by content targets for consistency, tone, inclusive language, and scannability.

Rytr- Rytr writes content in any tone and format, including email, ad copy, and automatically generates catchy and creative copy.

Clear communication

Writer-Writer, is an AI-controlled editing software for editorial offices. First the team needs to define its guidelines and then the AI ​​will identify any inconsistencies and mistakes in the attribution that can potentially damage the brand image.

Wordtune – Its deep tech understands what the user is trying to say and suggests ways to make the writing clearer, more persuasive, and more authentic.

Grammarly – Grammarly’s algorithms identify potential problems in the text and make context-specific suggestions to help with grammar, spelling and usage, wording, style, punctuation, and even plagiarism.

Hemingway Editor – The app highlights long, complex sentences and common mistakes along with adjective and phrase suggestions and formatting.

Academic writing

Ginger- In addition to spelling and grammar, Ginger considers entire sentences to suggest context-based corrections.

ProWritingAid – ProWritingAid provides clear, simple steps to improve your writing skills with specific creative, business, and academic annotations.


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