Call it a revolution or a challenge, artificial intelligence is now able to speak, listen, understand, and write the human language. If that’s not enough, let’s welcome natural language processing (NLP), which is one form of artificial intelligence that extracts sense from the human language for making information-based decisions. For the most part, the technology is still emerging, but it’s being processed in various ways. With this blog, we will be sharing insights into natural language processing and how it’s changing the job market!
What Jobs Require Natural Language Processing?
Well, in all honesty, humans don’t really pay much attention to the intricacies of our language. We regularly use semantic cues for conveying information through signs, words, and images. It’s a known fact that language is extremely easy to learn and comes naturally to humans. However, it’s extremely challenging for computers to understand the language. That being said, artificial intelligence and machine learning have led to the development of natural language processing.
With each passing day, the popularity of natural language processing is increasing. While most of us aren’t familiar, NLP is actually used in various applications that we use in our daily lives. In this section, we are outlining some jobs that use NLP, such as;
Email filtering is one of the most popular and basic jobs done by natural language processing. Initially, this job started with spam filters with which it would uncover the specific phrases and words that signal the spam email. However, with the integration of natural language processing, filtering techniques have improved. For instance, the email classification of Gmail is one such example of the NLP.
To illustrate, the Gmail system can identify if the email belongs to promotions, primary, or social tabs based on the contents of the email. When it comes down to the Gmail users, NLP ensures that the inbox remains manageable, and you only get to receive the relevant emails that need quick review and response.
“Siri, what is the weather temperature?” “Alexa, “turn on the bedroom lights!” Do these phrases sound familiar? Siri and Amazon Alexa are the smart assistants that identify the patterns in speech through voice recognition technology. It interprets the speech to respond. We all have become habitual of saying, “Hey Siri,” and ask our desired questions, and she is always there to respond.
For the most part, we expect these assistance tools to understand the contexts and cues since it improves the standards of living. Even more, we all love the humorous replies, and the interactions are extremely engaging. That being said, how do all these jobs take place? Yes, that’s right, natural language processing is behind these jobs!
We regularly use search engine platforms, and these engines use natural language processing for delivering the relevant results. The search engines deliver the results according to user intent and search behavior, which means there is no need to use the search-item wizards. To illustrate, Google can easily predict popular searching whenever you start typing.
However, the intriguing part is that it checks the full image and identifies what you want to say rather than using the search words. That being said, the search result jobs utilize the NLP for completing the search and delivering the most useful search results.
Ranging from predictive text to autocorrect and autocomplete, these features are widely available on smartphones, and we all have been taking it for granted, right? The predictive texts and autocompletes are similar to the search engines (predicting the things depending on typed content). As for autocorrecting, it tends to change the wording to ensure messages make sense.
These features use natural language processing to deliver sensible outcomes. The predictive texts will customize themselves for adding language quirks. Consequently, it delivers personal and relevant results.
Imagine being an English person visiting France or Spain per se; it’s going to be a mess, right? Generally, people use language translators, but they don’t make sense. This is because the translators don’t deliver the sentence structure. With natural language processing, the online translators can translate the languages accurately, and the results will be correct (yes, grammatically correct).
Digital Phone Calls
Whenever we call customer care services, they always say, “this call might be recorded for quality assurance or training purposes,” but did you ever pay heed to the calls? For the most part, these recorded calls are stored in the natural language processing system’s database for improvement and learning purposes.
The automated systems are widely used for directing customer query calls to the service representatives who provide helpful information. That being said, this is the job done by NLP, which is being used by large-scale telecommunication companies. In addition, it can also create a human-like voice even with computer-generated calls and language.
The natural language features are integrated into the data analysis since more vendors are now offering the natural language interface for visualizing data. For instance, visual encodings offer visualization according to data semantics. That being said, it opens up the streams of opportunities for exploring the data through natural language processing.
Text analytics is responsible for converting unstructured data into structured and meaningful data for analyzing purposes. It uses machine learning, linguistic, and statistical technologies. In this case, NLP can be implemented to improve customer interaction. Also, this analysis empowers the brands to experiment with the marketing campaigns.
Even more, the text analytic job can use the NLP for identifying structures in the unstructured data and keyword extraction. As a result, it can automate and manage small-scale tasks.
Data and information are extremely important in the digital era. However, there is always a chance of information overloading. For this purpose, natural language processing systems can help summarize the data and information to make it understandable. Also, it’s utilizable for creating an accurate and short summary for long data content.
Sentiment analysis is one job that NLP has on its should. Sentiment analysis is responsible for identifying the sentiments in the posts, and it can also determine sentiments where the emotions are expressed properly. That being said, NLP can be utilized for identifying the sentiments and opinions of their customers (yes, even from the online content). As a result, the companies get to understand the customers’ perception of their services and products.
What Skills Are Required For Natural Language Process Jobs?
Natural language processing a new addition to the tech world, and everyone is taking their sweet time to adapt to this new technology. However, some skills are essential for people who want to bag a natural language process job, such as;
- Statistics & Probability – a variety of models, such as n-gram language modeling, are designed on the guess basis. That being said, if you want to take the natural language process job, you will need to analyze and/or handle corpora.
- Linguistics – the sentences and information are composed with words and have certain rules and structures. If you are enthusiastic about taking the natural language processing job, you must understand the usage and features of verbs and nouns.
- Programming – natural language processing needs programming, so if you want to take such a job, you must know the programming languages. In addition, you must understand how programing codes should be implemented to complete the job (it’s best to learn Python).
- Recursive neural networking – this is the research type with which the candidates will be able to build the model with a corpora base. In addition, you must know how to train the models.
- Syntax – the NLP people have to teach the machines about human language nuances which means they must be aware of syntax, along with grammar and spelling
What Certifications/Training I Must Acquire For Getting Natural Language Processing Jobs
Microsoft: Explore Natural Language Processing
If you are a beginner and want to step into the NLP world, this is the optimal option. This course is focused on teaching the learners the basics of natural language processing. It leverages the Microsoft Azure platform for teaching the basics. Microsoft Azure has an extensive range of services, such as language understanding, translation, text analytic, and more which eases the development of NLP apps.
This course is a two-hour course with four modules. These modules include Translate text and speech, analyze text with the text analytics service, recognize and synthesize speech, and create a language model with language understanding.
Microsoft Certified: Azure AI Fundamentals
This course is a better option for advanced users and is designed by Microsoft. It allows professional and advanced-level professionals to understand machine learning and artificial intelligence concepts. In addition, this course allows them to master the workload and learn how Microsoft Azure can be implemented.
This course is responsible for teaching five skills, machine learning principles for Azure, artificial intelligence considerations and workloads, and computer vision workload features on Azure. In addition, it teaches conversational artificial intelligence workloads and features of natural language processing workloads. This course is great for people who have basic programming information.
PG Certification in Machine Learning and NLP (upGrad)
This is a six-month course which is perfect for the professional. This course offers around 250 hours of learning and is designed with five modules. The modules include exploratory data analytics and statistics, data science tool kit, machine learning, natural language processing, and machine learning II. The course also teaches Pandas, Python, Scikit-Learn, NLTK, Excel, and MySQL.
There are five industry projects, assignments, and case studies in this course. When students sign up for this course, they can get mentorship from industrial experts. In addition, it offers placement assistance to the candidates, so they can climb their career ladder.
Google Developers Certification
This is a beginner course that is designed to test the basic knowledge of integration and to function with machine learning techniques. It teaches students how to implement machine learning techniques for real-time solutions. This course is being offered by Google in association with TensorFlow.
The students must know about natural language processing, convolutional neural networks, and image data. In addition, the students must know the development of TensorFlow models through computer vision. It comes with the exam at the end, and if students pass it, they can get the certification.
Amazon: Machine Learning University course on Natural Language Processing
Amazon has launched an in-house machine learning university that delivers courses for machine learning practitioners. The learners will be able to expand their knowledge about the domain. The course is taught by Cem Sazara, and the learner can develop the data preprocessing, resources, and model evaluation understanding.
What Companies Are Using Speech To Text Or NLP Technology?
Nuance Communication was founded back in 2001 and is offering artificial intelligence and speech recognition products. These products are focused on the embedded speech recognition, server, automated telephone directory services, telephone call steering systems, and transcription systems.
Google is another company that uses natural language processing and google speech-to-text technology. Google tends to offer a variety of services, such as cloud computing, search engines, computer hardware, and online advertisement technologies. It is offering the speech-to-text feature for the conversion of speech into text through AI technology-powered API.
This is the company headquartered in Washington and is functioning in amazon web series, retail sales of subscription ad products, and North America. Amazon is focusing on advanced amazon transcribe technology, such as cloud computing, artificial intelligence, eCommerce, digital streaming, and consumer electronics. It’s easy to integration speech to text capacity.
Well, who doesn’t know about Apple? Anyhow, Apple is involved in the marketing, manufacturing, and selling of media devices, mobile phones, and computers. Apple has designed speech recognition that captures the users’ voice and sends it out to the servers for processing purposes.
IBM Corporation has been working since 1911 and is offering five key IBM Watson consulting service segments. These segments include the global business service, cognitive solutions, systems, and global financing, technology services, and cloud platforms. Coming to the point, they have speech recognition which enables the apps and systems for processing and understanding human speech.