Saturday, July 2, 2022

The Voice Recognition Market in 2022

Voice recognition, sometimes referred to as speech recognition, is a field combining linguistics and computer science. It enables machines and programs to receive speech as input and understand spoken commands.

Voice recognition technology is often used in tandem with artificial intelligence (AI) and machine learning (ML). It can be implemented to understand spoken words and phrases or for identifying a specific individual’s voice.

See below learn all about the global voice recognition market:

See more: Top Performing Artificial Intelligence Companies

Voice Recognition Market

The voice and speech recognition technology market was estimated at $7.7 billion in 2020. It’s projected to maintain a compound annual growth rate (CAGR) of 18.1% over the forecast period from 2021 to 2026, reaching $20.9 billion by the end of it.

The voice segment accounts for 27.8% of the market share and has an estimated CAGR of 22.6%.

Regionally, the voice and speech recognition technology market is divided as follows:

  • The U.S. market was estimated to be worth $2.9 billion in 2021, accounting for a 33.2% share
  • The Chinese market is forecast to reach $23 billion by 2026, maintaining a CAGR of 21.6%
  • Japan and Canada are expected to grow at 16% and 16.4% rates over the forecast period from 2021 to 2026
  • Within Europe, Germany has one of the highest CAGRs at 17%
  • The rest of the Europe is forecast to reach $2.8 billion by 2026

By industry vertical, the market is led by the banking, financial services, and insurance (BFSI) and health care sectors, globally. The automotive manufacturing industry is expected to see substantial growth in U.S.-based and European markets.

Other notable industry verticals include:

  • Consumer electronics
  • Retail
  • Military
  • Legal

Voice and speech recognition technologies have been implemented in consumer- and enterprise-grade devices for the past 10 years. However, it took more time for the technology to become sophisticated enough for users to depend on it in accomplishing tasks and conveying commands.

Since the intelligence of voice and speech recognition technology is theoretically infinite, it can be used to provide business services to a more diverse demographic. From understanding different accents and languages to the simple fact that people talk faster than they type, the future of voice and speech recognition in business is promising.

See more: The Artificial Intelligence (AI) Market

Voice Recognition Features

Voice recognition technology can have numerous applications from personal assistants to accessibility accommodation, in addition to boosting productivity and simplifying multitasking.

There are various types of voice recognition systems that receive and handle audio input differently depending on how they were trained. 

Speaker Independent Systems

Speaker independent voice recognition systems are able to detect and analyze a wide range of words and phrases, regardless of who is speaking.

They can recognize a variety of speech patterns, tones, and accents, and are often used in phone calls.

Speaker Dependent Systems

Speaker dependent systems are curated to the speaker’s voice and speech patterns. They rely on machine learning to continuously analyze and learn the way a specific person speaks, including tone , patterns, and accent.

This type of voice recognition system grows in accuracy over time, but only when it comes to the processing of a specific person’s speech and voice.

Discrete Speech Recognition

Discrete speech recognition systems take less time and effort to train, and they aren’t as versatile. Instead of attempting to understand a user’s speech, discrete systems only recognize sets of words and phrases.

Oftentimes, the speaker would need to pause briefly between words for the software to detect them. These systems are usually used in “command and control” applications, where there’s only a predefined set of instructions for the speaker to choose from.

Natural Language System

Natural language voice recognition systems use natural language processing (NLP) in combination with machine learning and artificial intelligence to understand natural speech.

Most commonly used in smart home assistants and smartphones, natural language systems can understand the natural speaking patterns, including tonal differences and various accents.

In terms of security, the previous types of voice and speech recognition systems can be paired with access or pass phrases. They would require the user to say a preset word or phrase that is compared to a base recording to verify the user’s identity.

Benefits of Voice Recognition

While the technology is still relatively new with plenty of room to grow and evolve in the upcoming years, voice recognition technology is already beneficial to companies.

A few benefits of voice recognition technology include:

  • Boosts productivity
  • Provides faster input and commands than typing
  • Real-time text-to-speech transcription
  • Disability accommodation
  • Real-time speech translation
  • Hands-free typing and command-entering
  • Voice recognition as identity verification

“There is a momentous boost in the adoption of voice and speech recognition among companies, as it becomes more deeply revealing,” says Edward Miller, member of the Forbes Technology Council.

“As banks, insurance companies and health care providers see and understand the value in using voice recognition to verify and authenticate customer identities, more and more businesses will employ voice biometrics to confirm the personal identity of any caller by the unique characteristics, pitch, cadence, and dialect of that person’s voice.”

Voice Recognition Use Cases

Voice recognition is a versatile technology that can put to use in a wide variety of industries to accommodate a company’s specific needs.

Voximplant

Voximplant is a technology company that provides a serverless communication platform for real-time voice, video, and messaging for business clients. Founded in 2013, it helps businesses worldwide answer millions of calls using its infrastructure.

In order to improve its offerings to its loyal clients, Voximplant sought to develop a voice recognition solution to scale up its operations globally. 

Using Google Cloud Speech-to-Text, along with Dialogflow, Voximplant was able to build a speech recognition and transcription functionality in over 120 languages, and deploy voice and text-based chatbots.

“Voice recognition and conversational interface functionality is available out-of-the-box on Google Cloud, and this has been key,” says Sergey Poroshin, Chief Development Officer and co-founder of Voximplant.

“Without it, we wouldn’t have been able to launch so many services for our clients. One example is freeform speech recognition, which is really hard to achieve,” adds Poroshin.

Moving to the cloud, Voximplant was able to process 1 million minutes of speech per month and reduce server setup time from two days to 30 minutes.

Witekio

Witekio is an international company and provider of embedded software technology for businesses in numerous industries. Based in France, Witekio has 5 offices and over 300 clients that it aids in low and high-level software implementation and training.

To meet the growing demand for voice-powered technologies, Witekio partnered with Vivoka on multiple projects with embedded voice recognition capabilities, such as professional appliances, smart vending machines, and a voice-operated, industrial crane.

“We partnered with Vivoka on several innovative projects on embedded Linux system, and delivered, in a very short time, multilingual natural voice interactions fully running “at the edge” to our customers,” says Cédric Vincent, Vice President of Technology at Witekio.

“With our expertise in Embedded Linux and Vivoka Voice Development Kit we can quickly customize and integrate their technology to demonstrate the benefit of speech recognition and text to speech for any type of product from industrial ovens to coffee machines,” adds Vincent.

Panama City Surgery Center

Panama City Surgery Center is an ambulatory surgery facility based in Panama City, Florida. A physician-owned facility, its 45 physicians run 4 operating rooms and 2 procedure rooms.

The center sees a large volume of patients, ranging from 800 to 900 per month. To better serve them, the clinic was looking to upgrade its patient documentation and medical records workflows.

Instead of relying on typing, Panama City Surgery Center contacted 3M and made the switch to the M*Modal Fluency Direct speech recognition-based system for its patient records. It was able to complete the full transition within a month.

“It’s moving us to the future. It makes everyone more self-sufficient. Not having to send notes for transcription brings us time savings, cost savings, and performance improvement,” says Kellee Manning, Organizational Management Officer at Panama City Surgery Center.

Working with 3M, Panama City Surgery Center was able to save anywhere from $18,000 to $24,000 per year on transcription fees. Additionally, most operative reports are ready within the same day and with outstanding accuracy.

Voice Recognition Providers

Some of the leading players in the global voice recognition industry include:

  • 3M Company
  • IBM
  • Google
  • Open Text Corporation
  • LumenVox
  • Sensory
  • Honeywell International
  • Nuance Communications
  • Sestek
  • Acapela Group

See more: Artificial Intelligence Trends

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