10 Natural Language Processing (NLP) APIs Posted in Platforms Vyom Srivastava October 27, 2022 Natural language processing (NLP) has gained a lot of momentum recently and is especially helpful for any business looking to automate its customer service. Conversational AI is the way forward, and Natural Language Processing is critical to that goal. Thankfully, there are several great NLP tools out there to help you build more conversational digital user experiences. Below, we’ll review ten of the top natural language processing APIs currently available on the market. How Do Natural Language Processing APIs Work? Natural language processing (NLP) APIs are a type of artificial intelligence that enable computers to understand human language. They do this using various techniques, including text analysis, classification, and natural language understanding. NLP APIs typically take text input, such as a sentence or paragraph, and return a list of results that include the meaning of the text, the sentiment of the text, and other information. Some NLP APIs also allow you to specify the context of the text, such as whether it is a question or a statement, which can help the computer better understand the meaning. 10 Natural Language Processing (NLP) APIs IBM Watson NLP IBM Watson NLP is a powerful natural language processing API that can help you analyze text and extract essential information. With Watson NLP, you can identify entities, sentiments, and keywords in the text and analyze syntax and structure. Watson NLP can also help you understand the relationships between entities in text. The IBM Watson NLP platform offers several benefits for developers, including the ability to: Access a variety of APIs that enable developers to build applications that can understand human language and interpret user intent. Process and analyze natural language data in the cloud using a variety of algorithms. Integrate with other IBM Watson services, such as the Watson Discovery service, to further enhance the functionality of applications. The IBM Watson NLP platform is an excellent choice for developers looking to build applications that can understand and interpret human language. AYLIEN AYLIEN is one of the leading NLP APIs. It offers various features and capabilities, including text analysis, sentiment analysis, and entity recognition. AYLIEN is used by some of the world’s largest companies, including Microsoft, IBM, and Google. Its text analysis features include topic classification, keyword extraction, and summarization. The sentiment analysis capabilities allow users to analyze text and detect positive, negative, and neutral sentiments. The entity recognition features can identify people, places, organizations, and other named entities in text. The API is easy to use and well-documented. It offers a free plan for small projects and paid plans for larger projects. Wit.ai Wit.ai is a natural language processing (NLP) API that allows developers to add intelligent, conversational features to their applications. Wit.ai understands human language and can interpret user utterances, allowing developers to create applications that can engage in conversations with users. Wit.ai offers several features that make it an attractive option for developers looking to add NLP capabilities to their applications: Wit.ai offers an easy-to-use interface that makes it simple to start with the API. Wit.ai provides developers with several tools and resources that they can use to build and train their models. It offers several different pricing options that make it affordable for developers of all budgets. Microsoft LUIS Microsoft LUIS is a cloud-based natural language processing API that enables developers to easily add pre-built language understanding to their applications. LUIS provides a variety of features that make it an ideal choice for NLP applications, including: Built-in support for various languages: LUIS supports multiple languages, making it easy to add language understanding to your applications. Customizable models: LUIS provides customizable models that allow you to tailor the language understanding to your specific needs. Integrated machine learning: LUIS constantly uses integrated machine learning to improve the accuracy of its language understanding. Easy to use: LUIS features a simple, intuitive interface that makes it easy to get started with language understanding. MindMeld MindMeld is an NLP API that allows developers to build applications that can understand human language. The API can process text, speech, and other forms of natural language. MindMeld provides several features that make it easy to develop NLP applications, including: A robust set of APIs for text processing, including tokenization, part-of-speech tagging, and named entity recognition. A powerful machine learning platform can train custom models for specific tasks. An intuitive interface that makes it easy to get started with MindMeld. The MindMeld API is an excellent choice for developers who want to build NLP applications. The API is easy to use and provides several powerful features that enable you to create sophisticated applications. Stanford CoreNLP The Stanford CoreNLP API is constantly being updated with new features and improvements, making it an excellent choice. The Stanford CoreNLP API is one of the most popular and offers a wide range of features for processing text data. Some of the most notable features include: Sentiment analysis Part-of-speech tagging Named entity recognition Constituency parsing Dependency parsing Lexalytics Several of these NLP APIs offer a variety of features and capabilities. One such API is Lexalytics, which provides several features that can be used to process and analyze text data, such as sentiment analysis, entity extraction, and topic classification. Sentiment analysis is a process of determining the emotional tone of a piece of text. It can be used to gauge the overall opinion of a text or to identify positive or negative sentiments. Entity extraction identifies and extracts named entities from text, such as people, places, organizations, and dates. Topic classification is assigning a text to one or more predefined categories or topics. Lexalytics offers several other features, such as text analytics, text mining, and text classification. These features can be used to extract information and insights from text data. Amazon Lex Amazon Lex is a great service for building conversational interfaces into voice and text applications. Amazon Lex uses cutting-edge deep learning algorithms for automatic speech recognition (ASR) to convert speech to text, and NLU to recognize the intent of the text. This allows you to build conversational bots that can accurately fulfill customer requests and queries. With Amazon Lex, you can build chatbots or voice bots that can have lifelike conversations with your customers. Amazon Lex uses the same deep learning technologies as Amazon Alexa to recognize user intent and enable real conversation. Some of the features provided by Amazon Lex: Automatic speech recognition (ASR) to convert speech to text. Natural language understanding (NLU) to recognize the intent of the text. Human-like conversation. Customizable voice and tone. Integration with popular messaging channels and platforms. Google Assistant API Google Assistant API is one of the most popular NLP APIs. This API has many features that make it ideal for developers who want to add NLP capabilities to their applications. Some of the key features of the Google Assistant API include: Automatic Speech Recognition (ASR): This allows the API to convert speech to text, which is then processed by the NLP engine. Natural Language Understanding (NLU): This allows the API to understand the meaning of the text to respond. Text-to-Speech (TTS): This allows the API to convert text to speech to be played back to the user. Context Awareness: This allows the API to understand the context of the conversation to provide a more relevant response. The Google Assistant API is a powerful tool for developers who want to add NLP capabilities to their applications. With its many features, it is sure to meet the needs of most NLP development projects. Lingua Robot API The Lingua Robot API is a powerful tool for natural language processing. It offers many features that can be used to process and analyze text data. Some of these features include: Tokenization: This feature allows you to break up a piece of text into smaller units called tokens. This is useful for tasks such as word counting and part-of-speech tagging. Stemming: This feature allows you to reduce a word to its base form. This is useful for tasks such as search engines, where you want to match different forms of a word (e.g., “running” and “ran”). Named Entity Recognition: This feature allows you to identify proper nouns in text, such as people, places, and organizations. This is useful for tasks such as information extraction and question-answering. Language Detection: This feature allows you to detect the language of a piece of text. This is useful for tasks such as machine translation and text classification. The Lingua Robot API is a powerful tool that can be used for a variety of NLP tasks. If you are working with text data, you should consider the Lingua Robot API. Final Words We hope you enjoyed our roundup of ten natural language processing APIs and hope it’s given you a better understanding of what tool to use. These NLP APIs can all generate a lot of insights, especially in applications where you’re dealing with a lot of text categorization.