Natural language processing (NLP) allows applications to interact with human language using a deep learning algorithm. NLP algorithms input language and can give a variety of outputs based on the learned required task. These outputs can include automatic summarization, language translation, part-of-speech tagging, parsing or grammatical analysis, and sentiment analysis, among others. NLP algorithms can also provide voice recognition and natural language generation, which converts data into understandable human language. Some examples of NLP uses include chatbots, translation applications, and social media monitoring tools that scan Facebook and Twitter for mentions. Natural language processing algorithms are an example of a deep learning algorithim and may be a pre-built offering in anAI platform.
To qualify for inclusion in the Natural Language Processing category, a product must:
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Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; and automatically organizes a collection of text files by topic.
IBM SPSS Text Analytics for Surveys software lets you transform unstructured survey text into quantitative data and gain insight using sentiment analysis. The solution uses natural language processing (NLP) technologies specifically designed for survey text.
IBM Watson Tone Analyzer is a service that uses linguistic analysis to detect three types of tones from text: emotion, social tendencies, and language style, emotions identified include things like anger, fear, joy, sadness, and disgust, identified social tendencies include things from the Big Five personality traits used by some psychologists includi openness, conscientiousness, extroversion, agreeableness, and emotional range and identified language styles include confident, analytical, and tentative.
Microsoft Language Understanding Intelligent Service (LUIS) is a service that enable user to quickly deploy an HTTP endpoint that will take the sentences being send and interpret them in terms of the intention they convey and the key entities that are present, it has a web interface that can custom design a set of intentions and entities that are relevant to an application and guide ser through the process of building a language understanding system.
NLTK is a platform for building Python programs to work with human language data that provides interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum.
Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text that supports the common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution these tasks are usually required to build more advanced text processing services and includes maximum entropy and perceptron based machine learning.
Sonix is an online platform that combines automated transcription and editing. We built the world's first AudioText Editor™ that allows users to edit audio in a revolutionary new way: Edit audio by editing text. Sonix integrates with Adobe Audition, Adobe Premiere, Final Cut Pro, Audacity, and Hindenburg.
Microsoft Linguistic Analysis APIs is a tool that provide access to natural language processing (NLP) that identify the structure of text and it provides three types of analysis:Sentence separation and tokenization, Part-of-speech tagging and Constituency parsing.
Part-Of-Speech Tagger (POS Tagger) is a piece of software that reads text in some language and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc., although generally computational applications use more fine-grained POS tags like 'noun-plural'.
Stanford Pattern-based Information Extraction and Diagnostics (SPIED) is a pattern-based entity extraction and visualization that provides code for two components, Learning entities from unlabeled text starting with seed sets using patterns in an iterative fashion and Visualizing and diagnosing the output from one to two systems.
Intelligent Service Robot is a dialog platform that enables smart dialog through various dialog-enabling clients, such as websites, mobile apps, and robots. Users can use domain-specific knowledge bases, configure their own knowledge base for customized smart dialogs and use Intelligent Service Robot to facilitate self-service through multi-round dialog. Intelligent Service Robot can also integrate with third-party APIs to enable complex scenarios such as order search, shipping tracking, and self-service returns
Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala it integrated with Hadoop and Spark, to be used in business environments on distributed GPUs and CPUs that aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers.
Frog is an integration of memory-based natural language processing (NLP) that tokenize, tag, lemmatize, and morphologically segment word tokens in Dutch text files, will assign a dependency graph to each sentence, will identify the base phrase chunks in the sentence, and will attempt to find and label all named entities.
IBM Watson Natural Language Classifier is a service that enables developers without a background in machine learning or statistical algorithms to create natural language interfaces for their applications, interprets the intent behind text and returns a corresponding classification with associated confidence levels and the return value can then be used to trigger a corresponding action, such as redirecting the request or answering a question.
Kapiche is an AI-powered text analytics solution for understanding customer and employee feedback at scale, enabling you to make the most impactful decisions for your business. Kapiche is designed to uncover the actionable insights in customer and employee feedback, from both your structured and unstructured data, enabling you to make strategic decisions that have the biggest impact on customer and/or employee satisfaction and overall revenue growth. Regardless of whether the data is from NPS, CSAT or CES surveys, call center log transcriptions, product reviews, or employee pulse surveys, Kapiche does the heavy lifting for your analysts, producing insights deeper, faster and more accurate than has previously been possible. You can get up and running with Kapiche in minutes. Use Kapiche to answer your strategic CX questions: - What can I do to improve customer experience? - How do I increase our NPS/CSAT/CES score? - Which customer issues should we prioritize? - What is the best way to reduce customer churn? - How do I reduce costs and grow our revenue? - How do we know our customer strategy is right?
Microsoft Web Language Model API is a REST-based cloud service that provide tools for natural language processing, using this API, users application can leverage the power of big data through language models trained on web-scale corpora collected by Bing in the EN-US market.
Natural language Understanding Toolkit (nut) is an implementation of Cross-Language Structural Correspondence Learning (CLSCL)