In the recent years, the field of natural language processing (NLP) has gained a lot of traction and is one of the most dominant areas in data science. NLP is a subfield of artificial intelligence (AI) which aids machines in processing and understanding the human language in any given context so that they can automatically perform repetitive tasks like summarization, machine translation, ticket classification, and many others. Along with various innovations from giant companies like Google, NLP has witnessed progression in precision, speed, and even methods that are relied on by computer scientists to resolve complex problems.
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With the invention of AI bots such as Alexa, Cortana, Siri, and Google Assistant the use of NLP has surged many folds. Scientists are currently focused on building models that can better comprehend human languages such as English, Hindi, Mandarin, Japanese, Spanish, etc. which are formally known as natural languages. Here are some trends projected to dominate in the natural language processing sectors in the upcoming years:
- With growing innovations in the field of AI, machine learning is expected to play a vital role in the natural language processing techniques, particularly in text analytics. In the future years, machine learning engine can be used to perform more thorough analysis by means of supervised and unsupervised learning.
- The continuous evolution of social media platforms clearly indicated that these platforms are going to take over an even more significant role in how companies make decisions. For example, at the time of a quarterly report, a company can depend on several NLP tools to monitor the customer reviews, feedbacks, and responses about their company on social media platforms and in the news.
- The rising pragmatic use of NLP can allow companies with large quantities of unstructured text or spoken data to tackle dark data problems and efficiently identify and collate them for insights.
- NLP is also expected to become more common in areas that need to understand user intent such as intelligent chatbots and semantic search. Along with the growing use of deep learning as well as unsupervised and supervised machine learning, the plethora of natural language technologies are expected to endure to mold the communication capacity of cognitive computing.
- NLP is likely to play a vital part in tracking and monitoring market intelligence reports to mine intelligent data for companies for forming upcoming strategies. From 2021, NLP is predicted to find applications in a wide range of business areas. Presently, this technology is extensively used in financial marketing. It is helpful in sharing comprehensive insights into tender delays, market views, and closings and extracting information from large data sources.
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Recent Developments in the Natural Language Processing Arena
The adoption of natural language processing is rapidly growing owing to rising demand for big data, data analytics, powerful computing, and enhanced algorithms. Several players in the natural language processing market are profoundly investing in various developments related to natural language processing.
For instance:
- In July 2019, Facebook AI and researchers from the University of Washington formulated methods to improve Google’s BERT language model and attain performance on par or beyond state-of-the-art results in SQuAD, GLUE, and RACE benchmark data sets.
- In April 2020, researchers from the Stanford University NLP have built Stanza, a multi-human language tool kit. This is tool kit is useful for those working with text from many locales—for instance, social media. It offers support for operating numerous precise natural language processing tools on 60+ languages and for retrieving the Java Stanford CoreNLP software from Python.
- In April 2020, researchers from Microsoft Research and Google AI have introduced new benchmarks for cross-language natural-language understanding (NLU) tasks for AI systems like named-entity recognition and question answering systems. Google's XTREME covers 40 languages and consists of 9 tasks, whereas Microsoft's XGLUE covers 27 languages and 11 tasks.
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Impact of COVID-19 on the Natural Language Processing Market
The abrupt rise of COVID-19 pandemic has made a severe impact on the growth of the global natural language processing market. As per a report by Research Dive, the global natural language processing market is estimated to garner $42,389.83 million, growing at a CAGR of 20.6% from 2020 to 2027. As the pandemic situation is relaxing, the demand for natural language processing solutions and services is growing owing to the surging need for enhanced customers experiences in several industries such as healthcare. Moreover, to facilitate digital transformation in work processes, several industries are already planning to implement a varied range of natural language processing solutions and services. Moreover, NLP is going to be one of the dominating technologies in Artificial Intelligence in the near future. All these factors are likely to boost the growth of the global natural language processing market in the coming years.
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