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  1. Stackups
  2. AI
  3. Text & Language Models
  4. NLP Sentiment Analysis
  5. CoreNLP vs Speechly

CoreNLP vs Speechly

OverviewComparisonAlternatives

Overview

CoreNLP
CoreNLP
Stacks19
Followers23
Votes1
GitHub Stars10.0K
Forks2.7K
Speechly
Speechly
Stacks4
Followers4
Votes6

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Detailed Comparison

CoreNLP
CoreNLP
Speechly
Speechly

It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities.

It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.

An integrated NLP toolkit with a broad range of grammatical analysis tools; A fast, robust annotator for arbitrary texts, widely used in production; A modern, regularly updated package, with the overall highest quality text analytics; Support for a number of major (human) languages; Available APIs for most major modern programming languages Ability to run as a simple web service
Real time; Fully streaming; React client; Javascript client; iOS client; Android client; Speech recognition; Natural language understanding; Easy to configure
Statistics
GitHub Stars
10.0K
GitHub Stars
-
GitHub Forks
2.7K
GitHub Forks
-
Stacks
19
Stacks
4
Followers
23
Followers
4
Votes
1
Votes
6
Pros & Cons
No community feedback yet
Pros
  • 2
    Easy to configure
  • 1
    Real-time visual feedback
  • 1
    Privacy options
  • 1
    Great SDKs for all platforms
  • 1
    Browser support
Integrations
Java
Java
JavaScript
JavaScript
Python
Python
React
React
React Native
React Native

What are some alternatives to CoreNLP, Speechly?

rasa NLU

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.

SpaCy

SpaCy

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.

MonkeyLearn

MonkeyLearn

Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

Jina

Jina

It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

Sentence Transformers

Sentence Transformers

It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.

FastText

FastText

It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.

Flair

Flair

Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.

Transformers

Transformers

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.

Gensim

Gensim

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.

Amazon Comprehend

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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