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Amazon Comprehend

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Amazon Lex

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Pros of Amazon Comprehend
Pros of Amazon Lex
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    • 7
      Easy console
    • 5
      Built in chat to test your model
    • 2
      Easy integration
    • 2
      Great voice

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    Cons of Amazon Comprehend
    Cons of Amazon Lex
    • 2
    • 5
      English only

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    What is 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.

    What is Amazon Lex?

    Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.

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    What companies use Amazon Comprehend?
    What companies use Amazon Lex?
    See which teams inside your own company are using Amazon Comprehend or Amazon Lex.
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    What tools integrate with Amazon Comprehend?
    What tools integrate with Amazon Lex?

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    What are some alternatives to Amazon Comprehend and Amazon Lex?
    IBM Watson
    It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine.
    It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
    rasa NLU
    rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
    It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
    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.
    See all alternatives