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Based on our record, Wit.ai should be more popular than FuzzyWuzzy. It has been mentiond 23 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Hello everyone, new to LLMs. I am working on my thesis project. The whole idea is to create a mixed reality voice assistant that can control some devices in a room and you can have with it a more intelligent conversation compared to other voice assistants(Alexa,Google, etc.). I thought initially to use wit.ai for the extraction of commands and if it's not a recognized command to send a request to a chatgpt API.... Source: 5 months ago
I can't find anything wrong with the code you posted. It is possible that wit.ai is expecting some default header that Unity is not sending (and that you are not setting). Source: about 1 year ago
Even though this was made for VR hopefully the scripts for wit.ai and GPT will be helpful to anyone who wants to explore this topic and doesn't know where to start. Source: about 1 year ago
Hey HN, We're Alex, Martin and Laurent. We previously founded [Wit.ai](http://wit.ai/) (W14), which we sold to Facebook in 2015. Since 2019, we've been working on Nabla (https://www.nabla.com), an intelligent assistant for health practitioners. When GPT-3 was released in 2020, we investigated it's usage in a medical context[0], to mixed results. Since then we’ve kept exploring opportunities at the intersection of... - Source: Hacker News / about 1 year ago
Thank you, that's helpful except that currently we're not running our own server. I'm currently using wit.ai for NLP which is a web API service provided by Meta. I'm trying to budget for what it would cost to roll out our own on a private cloud. Source: about 1 year ago
Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 1 year ago
Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 1 year ago
It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: almost 2 years ago
You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 2 years ago
To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: almost 3 years ago
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Amazon Comprehend - Discover insights and relationships in text
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spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
Microsoft Bot Framework - Framework to build and connect intelligent bots.
Microsoft Bing Spell Check API - Enhance your apps with the Bing Spell Check API from Microsoft Azure. The spell check API corrects spelling mistakes as users are typing.