This is the next and last part of my previous article. Little recap is here in case you have missed it.

In the previous part, I have talked about cognitive computing, services, and Watson API’s. I have already covered Speech/Voice and Visual API in the previous part. Now I am going to describe how Language Processing API does work.

LANGUAGE API

1. Conversation

Conversation service helps to create an application that understands natural-language input and uses machine learning to simulate human and respond to customers. It is out of box solution and allows you to quickly build, test and deploy a bot or virtual agent across mobile devices, messaging platforms or physical robot. The conversation has a visual dialog builder to help you create natural conversations between your apps and users, without any coding experience required.

Supported Language: Brazilian Portuguese, English, French, Italian, Spanish, German, Traditional Chinese, Simplified Chinese, and Dutch. Arabic ,

2. Natural Language Classifier

Natural Language Classifier service uses machine learning algorithms to return the top matching predefined classes for short text inputs. The service understands the intent behind the text and returns a corresponding classification with a confidence score. It can help your application understand the language of short texts and make predictions about how to handle them. It can be used to answer questions in a call center, create chat bots, categorize volumes of written content and much more.
It involves following steps:

• Prepare training data
• Identify class labels
• Collect representative text
• Match classes to text
• Create and train classifier
• Use API to upload training data
• Query the trained classifier
• Use API to retrieve data
• Evaluate results and update training data

Supported Language: English, Arabic, Brazilian Portuguese, French, German, Japanese, Italian, and Spanish.

3. Natural Language Understanding

Natural Language Understanding can analyze semantic features of text input, including – categories, concepts, emotion, entities, keywords, metadata, relations, semantic roles, and sentiment. It categorizes content using a five-level classification hierarchy. View the complete list of categories here.

Full tutorial for Natural Language Understanding
Watson Knowledge Studio can be used to customize annotation models, identify industry/domain specific entities and relations in unstructured text.

4. Retrieve and Rank

Retrieve and Rank helps us getting most relevant information from a collection of documents. Retrieve and Rank service combines two information retrieval components in a single service: the power of Apache Solr and a sophisticated machine learning capability. This combination provides users with more relevant results by automatically reranking them by using these machine learning algorithms.

How it works:

• Collect and load content
• Collect content
• Modify and upload Solr configuration file
• Upload content
• Train the machine learning rank model
• Collect queries and relevant answers to leverage as training data
• Create and upload training data
• Query service
• Send runtime queries to trained model
• Evaluate results and improve model

5. Tone Analyzer

Tone Analyzer service uses linguistic analysis to detect communication tones in written text. It helps understanding tone in three general categories: emotional, social, and language AND seven categories specific to customer service & support conversations – Sad, Frustrated, Satisfied, Excited, Polite, Impolite and Sympathetic. The score ranges from 0-2 for each category that indicates the probability of tone the content. It can be used to understand communications and respond to customers appropriately.

6. Personality Insight

Personality Insights service allows applications to extract personality of individuals from any content like – social media, enterprise data, or other digital communications like email, text messages, tweets, and forum posts. The service uses linguistic analytics to infer individuals’ personality characteristics, including Big Five, Needs, and Values. It can also find out individuals’ consumption preferences about various products, services, and activities. Personality Insights service can help businesses understand their customers or clients at a deeper level by understanding clients’ preferences. And it can be used to improve client acquisition, retention, and engagement, and to guide highly personalized engagements and interactions to customize their products, services, campaigns, and communications for individual clients.

7. Document Conversion

Document Conversion service can transform a single HTML, PDF, or Microsoft Word document to normalized HTML, plain text, or a set of JSON-formatted content that can be used by other services, like Retrieve and Rank, Personality Insight, conversation etc.

Supported language: English, French, German, Japanese, Italian, Brazilian Portuguese, and Spanish.

8. Language Translator

Language Translator translates text from one language to another. The service offers multiple domain-specific models that can be customize based terminology and language. The service can be trained and customized over time to provide better accuracy. Watson learns from previous translations. The service takes specific terms and phrases into accounts, such as the names of people or products to ensure that they are translated correctly.

Supported language:
News: Translate English to and from Arabic, Brazilian Portuguese, French, German, Italian, and Spanish. Spanish to and from French.
Conversational: English to and from Arabic, Brazilian Portuguese, French, Italian, and Spanish.
Patents: Targeted at technical and legal terminology. Brazilian Portuguese, Chinese, and Spanish to English.

Conclusion

Independently the services listed are just sufficient for few use cases but together it can solve large business problems and can challenge and disrupt many existing business models. In subsequent articles, we will share about Watson Knowledge Studio, Watson Discovery, and Watson Explorer. We will also share the real-time use cases of AI in multiple businesses.