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:
Natural Language Processing (NLP) reviews by real, verified users. Find unbiased ratings on user satisfaction, features, and price based on the most reviews available anywhere.
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.
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.
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.
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.
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.
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.
Great businesses are built on two key pillars: a highly capable and engaged workforce and customers that love you. Sounds simple right? But when you have 1,000's of employees and customers, how can you get the understanding of the key issues affecting them to make the most impactful decisions possible? Enter Kapiche, 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. At the heart of Kapiche is a state of the art AI-powered Natural Language Processing and Analytics engine hosted on Azure, capable of ingesting and analyzing thousands of structured and unstructured text data points in seconds to find the actionable insights. Unlike other solutions, Kapiche doesn't need any complicated setup or customization to your particular data domain or business. 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 prioritise? - 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? Kapiche’s advanced AI technology will help you drive long-term revenue growth by quickly identifying and addressing those customer or employee issues that are having the biggest impact on your chosen CX or EX metric with confidence.
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.
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)
All the talk about qualitative data analysis is for naught if you can’t understand language as it is spoken. That is what Natural Language Processing (NLP) is all about. NewSci NLP brings this power to organization’s seeking to extract insights from their unstructured data. Just as you know what a person is saying when you hear, “I’m hungry, I want an apple” vs. “I really want an Apple™ instead of a PC,” so now can a computer. NewSci NLP enables a computer to understand the people, places, and things important to your organization. This, in turn, allows your unstructured data to be analyzed just like your structured data. With NewSci NLP your organization will enjoy qualitative analysis (the Why behind the numbers) alongside your quantitative analytics. Uses models customized to your organization; the domain in which you operate; the quality of your recordings; and even local and regional dialects to deliver the highest level of transcription accuracy. Captures your organization’s domain and unique characteristics to enable deep Natural Language Understanding analysis and Natural Language Generation. Your NewSci Ontology will be your Rosetta Stone for unlocking the value hidden in your unstructured data. The NewSci Insight Reservoir™ brings governance and insight to the data lake. You enjoy all the benefits of a state-of-the-art Big Data lake including access to hundreds of data connectors for ingesting information; transformation tools for quality assurance and data enhancement; and cataloging of your data down to the field level while at the same time having unmatched data governance capabilities: Unlike a passive data lake, the NewSci Insight Reservoir™ is a powerful cognitive computing platform where you can perform machine learning; deep learning; and natural language processing on all your structured and unstructured data. NewSci NLP connects directly to your NewSci Insight Reservoir™ to extract meaning from your text and make it available for analysis. Machine and Deep Learning algorithms can be created, and perfected, as data enters the Insight Reservoir™, increasing the value in real-time. And all of the insights can easily be made available for visualization tools including Tableau®, Qlik®, and MS Power- BI®. Jump out of the data lake and get your organization into the NewSci Insight Reservoir™
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.
Stanford CoreNLP provides a set of natural language analysis tools that can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract open-class relations between mentions, etc.