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prose

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Wit

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prose vs Wit: What are the differences?

Developers describe prose as "A Golang library for text processing". prose is a natural language processing library (English only, at the moment) in pure Go. It supports tokenization, segmentation, part-of-speech tagging, and named-entity extraction. On the other hand, Wit is detailed as "Natural Language for the Internet of Things. Turn speech into actionable data". Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.

prose and Wit can be primarily classified as "NLP / Sentiment Analysis" tools.

Some of the features offered by prose are:

  • Tokenizing
  • Segmenting
  • Tagging, NER

On the other hand, Wit provides the following key features:

  • Voice-enabled Android and iOS apps
  • Rasberry Pi based home automation commanded by speech
  • Google Glass apps accepting voice commands

prose is an open source tool with 2.02K GitHub stars and 95 GitHub forks. Here's a link to prose's open source repository on GitHub.

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What is prose?

prose is a natural language processing library (English only, at the moment) in pure Go. It supports tokenization, segmentation, part-of-speech tagging, and named-entity extraction.

What is Wit?

Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.

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    What tools integrate with prose?
    What tools integrate with Wit?
    What are some alternatives to prose and Wit?
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    It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
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    Amazon Comprehend
    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
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