Impact of Artificial Intelligence on Text and Speech Recognition Technology


The development of Artificial Intelligence (AI) and voice recognition has had a profound impact on almost every area of human existence. One technology that has benefited from AI’s ability to streamline processes is speech recognition. We can now convert voicemails to text with this cutting-edge technology. It can also teach your speech so you can issue commands with only your voice. The relevance of this AI-driven voice recognition technology skyrocketed as a result, especially among the likes of Apple, Microsoft, Amazon, Google, Facebook, etc. Many new applications and gadgets have recently hit the market with built-in voice recognition capabilities. 

Voice assistants are predicted to surpass humans in a few years; according to Statista, by 2024, the number of voice assistants could double to 8.4 billion from 4.2 billion in 2020. Each individual will use multiple voice assistants. 

AI in Speech Recognition Technology 

Using Artificial Intelligence and Machine Learning, voice recognition is quickly overcoming the obstacles of inadequate recording equipment, noise cancellation, variances in people’s voices, accents, dialects, meanings, situations, etc. In addition, there are difficulties associated with deciphering human nature and the many linguistic quirks that make up human speech. The technology is now on a level with everyday human conversation after achieving a rate of 95% accuracy in voice recognition. 

Furthermore, because many big corporations support and actively use voice recognition, it is now a valid mode of communication. It’s predicted that most search engines will include speech technology in their primary search interface. 

Artificial Intelligence (AI) and Machine Learning (ML) algorithms have advanced to the point where they can now analyze enormous datasets and provide much-increased accuracy via self-learning and adapting to new circumstances. Using complex and random data that is easily available for mining and Machine Learning, machines are taught to “listen” to a variety of human speech patterns, including dialects, settings, emotions, and more. 

Use Cases of AI in Speech Recognition Technology 

Let’s have a look at how voice recognition software is being put to use in various industries: 

  • Voice-activated speech recognition software is now widely utilized for various tasks, including making purchases, sending emails, transcribing meetings, hospital visits, court processes, etc. 
  • Voice recognition software is used by digital assistants and smart home devices to do tasks such as answering queries, playing music, checking traffic and weather, placing orders, and more. 
  • Voice-activated payment systems are now available from companies like Venmo and PayPal. Several financial institutions in the United States and Canada provide voice-based internet banking services. 
  • Voice-enabled virtual assistants play a crucial role in e-commerce, enabling customers to make transactions with little friction and maximum efficiency. 
  • Scheduling, routing, and navigating between cities are all areas where speech recognition has the potential to improve transportation services. 
  • Voice recognition software can transcribe audio recordings such as podcasts, meetings, and journalist interviews. It’s also utilized to caption a video correctly. 
  • Voice biometrics, in which a person’s voice is profiled by analyzing its frequency, tone, and pitch, has significantly affected safety. Swisscom, a Swiss telecom operator, has used voice authentication technology in its contact centers to avoid data breaches. 
  • It is becoming more common for chatbots and voice assistants powered by Artificial Intelligence to be used in customer support settings.

Law enforcement, marketing, tourism, content development, and translation are just some of the other fields pouring resources into voice-based speech recognition systems. 

AI in Text  

AI text analysis is the simple action of gleaning information from massive volumes of textual records. Natural Language Processing (NLP) is how computer software learns to comprehend and use such information. In order to make data-driven choices on how to serve customers better, companies may benefit from using Natural Language Processing to automate the process of analyzing client comments on a massive scale. 

Use cases of AI in Text 

  • Predictive Analytics to Verify Surgical Intervention 

The field of healthcare will significantly benefit from predictive analytics. Occasionally, we have patients who claim they endured a needless operation since no one could have foreseen the severity of their condition. Fortunately, advances in AI are altering the outcome of these undesirable hazards and unnecessary procedures. Healthcare providers may now determine whether or not a patient requires surgery using AI and predictive analytics. This technology will aid physicians in deciding whether surgery is really essential or if there is a safer option. 

  • Using AI for Infectious Illness Diagnosis 

Doctors have complained for the last year and a half that the government should have taken more measures to restrict the coronavirus when it first learned of its devastating impact. Nobody knew the severity of Covid-19′ is a common refrain. As a result, AI and other disruptive technology may be utilized to anticipate pandemics. The current method of diagnosing infectious illnesses may be improved with Machine Learning and big data. Doctors may do genetic tests using a proprietary database and ML algorithms to determine the contagiousness of the disease. 

  • Medical Aid in the Form of Mobile Applications 

Artificial Intelligence is aiding patients in their day-to-day care, whether at home or in the workplace, complementing the traditional medical services provided by hospitals and healthcare institutions. A profusion of health-tracking applications is available on both the App Store and the Google Play Store. The healthcare apps use voice assistant technology to remind users to take their pills and track their vitals. Patients are constantly reminded of the importance of their health care via the delivery of notifications and educational materials. 

  • Insurance Risk Detection Using Natural Language Processing 

The insurance industry is one that heavily depends on statistics. Before beginning the insurance application process, they investigate the applicants’ histories. Insurers analyze massive datasets in search of high-risk customers so they can provide more secure coverage. Insurers can examine vast amounts of text for factors impacting individual claims and actions using natural language processing. 

  • Use of Artificial Intelligence for Identifying Fraud 

The potential for fraud in banking and financial institutions is relatively high. The volume of business nowadays makes it impossible for human staff to monitor it all, much alone spot and prevent harmful material or questionable payments. In contrast, Machine Learning systems can examine hundreds of data points in real-time, flagging suspect or outright fraudulent transactions and preventing many false claims. 

  • Financial Investments Benefit from Machine Learning 

Artificial Intelligence and other disruptive technologies are being integrated into the operational systems of banking and financial organizations to perform predictive jobs as technology advances. One example of such foresightful activity is choosing the optimal investment strategy or location. Technologies powered by Machine Learning provide superior market insights, enabling fund managers to see granular shifts in the market far sooner than was previously possible with conventional investing strategies. 

  • Use of Artificial Intelligence to Improve Layout 

Artificial Intelligence (AI), programmable shading, and real-time ray tracing are employed extensively to revolutionize the conventional product design process. With the help of cutting-edge AI, a new ecosystem has emerged, speeding up the development of innovative design processes and enhancing teamwork in the process. Artificial Intelligence algorithms that define product concepts and the issue at hand may supposedly provide an infinite number of design iterations, making them the future of automobile design. 

  • Industrial Use of Artificial Intelligence 

In order to carry out industrial and supply chain operations, businesses deploy AI-based robots in tandem with human workers. Manufacturing using AI-powered robots has produced successful outcomes in material handling, performance testing, and product packaging. Robots are given the task of using their deep learning systems to discern which components to choose and how to pick them, speeding up the assembly process and allowing more automobiles to be produced daily. 

  • Utilizing AI for Quality Assurance 

Vehicles that have been painted are inspected using AI as part of quality control. As with many things requiring extreme precision, human error is not out of the question when making such detections. Artificial Intelligence allows robots to spot flaws more accurately and accurately than people. Machine Learning quality inspection is expected to replace the existing method of detecting cracks in materials using light. 

  • Enhancing Access to Search Results 

While it’s convenient to easily access a wealth of online data, finding specific information may be challenging. With the help of AI, finding what you need on the web and using suggestions is simpler and more reliable than before. For instance, you may use an image file upload instead of the film’s title to see a movie. Instead of guessing the name of a song by entering a string of random letters, you can play the music, and the streaming app will tell you what it is. 

Future of AI in Speech and Text Technology 

Speech recognition in AI is one of the most impressive technical progress results. With automated technologies like Siri, Alexa, Echo Dot, Google Assistant, and Google Dictate making our lives simpler, their popularity is only expected to rise. 

Automation services such as voice recognition are a popular strategy among businesses throughout the globe because it helps them save time and money, boost output and precision, and allow them to base choices on empirical evidence gleaned from analyzing consumer patterns and preferences. 

Rapid growth has been witnessed across the board in the global economy due to developments in Artificial Intelligence. In 2030, it is predicted that AI will add $15.7 trillion to the worldwide economy, which is more than the combined production of China and India. 

The potential of automatic voice recognition is quite exciting. According to rumors, Apple is developing an Apple TV that Siri can operate. A rise in the popularity of high-tech wristwear like smartwatches, headphones, jewelry, and voice-based software that can understand the context of a user’s requests to better respond to them is also being anticipated. 

Due to the widespread influence of voice recognition and AI in the home and business, there is likely to be a record-breaking need for qualified AI engineers and developers, Data Scientists, and Machine Learning Engineers. 


The time and effort saved by using speech recognition software solutions enabled by AI technologies like NLP and ML to do mundane jobs are immeasurable. Benefiting from these features may help save time and effort. The convenience and effectiveness of voice-activated technology are welcome additions to consumers’ lives at home and in the workplace. Jigsaw Courses are worth a look if a career in this area is something you’re interested in. It’s obvious that the skyrocketing AI industry needs as much workforce as it can get. If you’re interested in riding the AI wave, UNext Jigsaw can offer you an opportunity with its Management and AI program.

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