Abstract:In this paper we have a look at the various application tools of NLP applied in the field of Civil Aviation. Civil aviation flights around the world are in huge demand. Order books of major Aircraft manufacturers such as Boeing, Airbus, Embraer etc are overflowing and delivery schedules for the next few years are full. In WINGS INDIA 2018 held at Hyderabad, Airbus reported that for the next 10 years India will be receiving one Airbus aircraft every week [1][2] [3]. More aircrafts leads to more pressure on maintenance teams, ATC (Air Traffic Controller), ground marshals / crew and CNS (Communication Navigation Surveillance) handlers. MRO (Maintenance Repair and Overhaul) units by Boeing, Airbus, ATR apart from simulator Training units are coming up fast in countries like India, China, Srilanka and other countries, which calls for more automation of the day to day technical and maintenance works . NLP (Natural Language Processing) and AI (Artificial Intelligence) tools have been playing just the required role in a remarkable manner in managing incident reports, CNS assistance etc. The supporting role of NLP in maintenance, real time situation awareness and other areas are going to be a necessity in the foreseeable future.

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E-dictionaries, quite common today are available for multiple languages in monolingual, bilingual and multilingual forms. In NLP they form the core of a series of tools that are used to understand words, sentences and in turn the language itself. These E-Dictionaries work well for any language domain as a whole. For almost all languages E-dictionaries are available, but once specialized technical domains are encountered these E-Dictionaries are quite useless. Aviation is one such specialized domain for which no E-Dictionary, translation or transliteration tool exist. On the other hand the need for such tools for specialized domains are increasing. The tool discussed in this paper is an attempt to bridge the gap that currently exists between English and Bengali languages.

English is a language that is understood, spoken and used by citizens of a diverse array of countries. The speakers include both native and non-native speakers of English. NLP or Natural Language Processing on the other hand is a branch of computer science that deals with one of the most challenging aspect that a machine can process: dealing with Natural Languages. Natural languages which have evolved over centuries are complete, diverse and highly complex and thus are challenging for a computer system to understand and process. MT or Machine Translation is a more specific part of NLP that translates one natural language to another (English being one of the major researched and sought after languages among them). Though research in the field of NLP and MT has come a long way and many efficient translators are available, still Translation and other NLP applications in specialized domains such as aeronautics are still today a challenge for NLP researchers and developers to achieve. NLP applications are often used in education of English Language, and are therefore a continuous process for Non-Native speakers of English. Non-native English speakers take help of various NLP tools such as E-Dictionary, MT applications and others to better understand the English language and thus learn it better and faster. Aviation English poses a challenge to MT systems and understanding it as a whole requires specialized handling as it has own phonetic pronunciations and terminologies and constituent Out-Of-Vocabulary words. Dealing with Aviation English calls for teaming up of experts from Applied Linguistics, NLP and AI. As a result it becomes a cross-research discipline that covers situations that demand real time use of proper language, e.g. ATC communications. This Paper aims to discuss most recent research methodologies that deals with the Aviation English and reviews the problems posed by it. Being a specialized and structured form of English, the problems are faced by both native and non-native speakers of English Language. Discussion is carried out in the relevant and recent advances of methods in dealing with aviation English language challenges from both, the Human (ICAO/DGCA/AAI) as well as NLP angle. Lastly we have a look at how these challenges are linked to scope for development of applied technologies. Research in experiential Aviation English situations deals with both English for Specific Purposes - ESP (Aeronautics in our case) as well as situations in English as a Foreign Language i.e. EFL (English-Indian language pair).