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It is a unified, developer-friendly API to the best available Speech-To-Text and Text-To-Speech services. | 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. |
Build voice-enabled chatbot services (for example, IVR systems); Classification of audio file transcriptions; Automated Testing of Voice services with Botium | Real time; Fully streaming; React client; Javascript client; iOS client; Android client; Speech recognition; Natural language understanding; Easy to configure |
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GitHub Stars 943 | GitHub Stars - |
GitHub Forks 58 | GitHub Forks - |
Stacks 7 | Stacks 4 |
Followers 21 | Followers 4 |
Votes 0 | Votes 6 |
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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 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.

Convert text to high-quality AI voice in seconds. Perfect for content creators, businesses, educators and video makers. Fast, affordable and studio-grade output with multiple accents and languages.

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.

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.

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.

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.

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.

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.

Plan, write, and publish books, PDF guides, workbooks, and audiobooks with AI workflows. Customize branding and export instantly.