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NLP as a Service

Introduction to NLP technologies

Natural language processing (NLP) refers to the branch of AI concerned with giving computers the ability to process, understand and generate human language. NLP combines computational linguistics (rule-based modelling of human language) with statistical, machine learning and deep learning models to bridge the communication gap between humans and machines.

Figure 4. NLP technologies

NLP encompasses a wide spectrum of technologies designed to be integrated into diverse user experiences. It includes deterministic and probabilistic techniques, syntax and semantics methods, named entity recognition (NER), etc.

Nowadays, the use of NLP in virtual assistants is not limited to understand and respond to simple utterances but also to derive meaning and use data behind user queries, allowing them to provide relevant and precise responses resulting in more accurate and natural interactions through different NLP technologies.

Application of NLP as a Service in ATRIA

NLP as a Service enables the use of different technologies through NLP Apps (Natural Language Processing recognition stages) for understanding users’ requests and providing back accurate responses.

Currently, these technologies, both proprietary and third-party ones, are included in the Aura NLP component but, in future releases, external NLP methods will be used.

In this framework, constructors have two approaches depending on the utilized stages:

• Using NLP Apps (NLP recognition stages) different from Semantic Search
  Find here detailed information regarding NLP Apps capability

• Using Semantic Search technology, a specific NLP App that overcomes traditional keyword-based searches through the use of embeddings.
  Find here detailed information regarding Semantic search functionality

Figure 5. NLP as a Service in ATRIA

Benefits from the use of NLP as a Service

NLP as a Service offers several benefits both for constructors and end-users:

Benefits for use cases constructors

• Less time and complexity of use cases development
• It is possible to create and configure tailored NLP pipelines, choosing from a variety of available stages and connectors that cover different aspects of Natural Language Processing.
• No need for the manual generation of training phrases (aliases) for generic questions knowledge bases.
• Knowledge bases can be updated continuously in an easy and quick way.
• Accessibility: any application, both internal and external to Aura Platform, can consume this service.

Benefits for Aura end users

• End-users can interact with Aura in a natural and conversational way, using their own words and expressions and even informal language, slang, abbreviations, misspellings, etc.
• Improved Aura’s understanding capabilities, leading to fast and reliable responses and results.
• Easy update of the knowledge bases, so the users can receive reliable responses based on up-to-date data.
• The NLP service can be leveraged as capabilities offered to end-users or as internal features used by other Telefonica teams in order to streamline specific internal processes.