About two decades ago, no one would have believed that the technologically advanced make-believe world of ‘Star Trek’ that pushed the frontiers of imagination could come true – so soon. The voice recognition technology behind the conversational assistant that helped Captain Kirk navigate the stars is now helping us find the way to the nearest grocery store or the best restaurants.
In less than twenty years, voice recognition technology has grown phenomenally. But what does the future hold? In 2020, the global voice recognition technology market was about $10.7 billion. It is projected to skyrocket to $27.16 billion by 2026 growing at a CAGR of 16.8% from 2021 to 2026.
The phenomenal growth of voice technology can be attributed to several factors. Some of these are the increase in the adoption of electronic devices, the development of voice-operated biometrics, voice-driven navigation systems, and advancements in machine learning models. Let’s dig deeper into this emerging technology and understand its workings and use cases.
What is Voice Recognition?
Voice recognition, otherwise known as speaker recognition, is a software program that has been trained to identify, decode, distinguish and authenticate the voice of a person based on their distinct voiceprint.
The program evaluates a person’s voice biometrics by scanning their speech and matching it with the required voice command. It works by meticulously analyzing the frequency, pitch, accent, intonation, and stress of the speaker.
While the terms ‘voice recognition and ‘speech recognition are used interchangeably, they aren’t the same. Voice recognition identifies the speaker, while the speech recognition algorithm deals with identifying the spoken word.
Voice recognition has grown tremendously over the past few years. Intelligent assistants such as Amazon Echo, Google Assistant, Apple Siri, and Microsoft Cortana perform hands-free requests such as operating devices, writing notes without using keyboards, performing commands, and more.
How Does Voice Recognition Work?
The speech recognition technology undergoes a few steps before it can reliably ascertain the speaker.
It starts by converting analog audio into digital signals. To figure out what you are asking, the voice assistant, the microphone in your device, pick up your voice, converts those into electrical currents, and converts those analog sounds into digital binary format.
As the electrical signals flow into the Analog-to-Digital Converter, the software starts picking up samples of voltage variations in certain parts of the current. The samples are small in duration – amounting to barely several thousandths of a second long. Depending on the voltage, the converter will assign binary digits to the data.
To decipher the signals, the computer program needs an elaborate digital database of vocabulary, syllables, and words or phrases and a quick method of matching the signals to data. The comparator compares the sounds from the stored database against the audio-to-digital converter using a pattern recognition action.
Voice Recognition – The Advantages and Disadvantages
|Voice recognition allows multitasking and hands-free comfort.||While voice recognition technology is improving by leaps and bounds, it is not completely error-free.|
|Talking and giving voice commands is much faster than typing.||Background noise can interfere with the working and impact the reliability of the system.|
|The use cases of voice recognition are expanding with machine learning and deep neural networks.||The privacy of the recorded data is a matter of concern.|
High-quality Speech / Voice Datasets to Train Your Conversational AI Model
Use cases of Voice Recognition
Voice recognition systems are used for several applications. Speaker recognition is generally divided into three major categories – detection, verification, and segmentation.
Voice Recognition for Authentication
Voice recognition is predominantly used for biometric person authentication, where a person’s identity is established using their voice.
Other forms of identity authentication solutions, such as key or credit card passwords, can be lost, forgotten, or stolen. However, the speaker recognition system is much more credible and foolproof when compared with passwords or PINs.
Voice Recognition for Forensics
Another important application of voice recognition technology is the application in forensics. If a speech sample was recorded during the commission of the crime, it can be compared with the suspect’s voice to find any similarities between the two.
Voice Recognition for Financial Services
Voice or speaker recognition is proving itself very useful in financial services for verifying the identity of callers. Many banks have added voice biometrics as a secondary level of user authentication.
Voice recognition adds another layer of security, especially for banks and financial institutions needing a secondary reliable authentication method.
Voice Recognition for Security
One of the most prominent benefits of voice recognition is security. Speaker recognition provides transaction authentication, access control, long-distance telephone banking user authentication, and monitoring to eliminate misuse of information.
Additionally, intelligent voice recognition systems could also reject unauthorized access to critical information or databases. For instance, if a child tries to access a voice-enabled payment service, it would be rejected since it can’t be authorized.
Voice Recognition in the Retail Industry
Speaker recognition is being used extensively in the retail and e-commerce industry to conduct voice searches, and accurately identify and authenticate users.
Voice Recognition for Healthcare
Voice recognition plays a significant role in enhancing the nature and quality of care provided to patients. Patients’ voice biometrics is being used to authenticate their identity in their databases, to avoid legal tangles, and continue to provide continued healthcare services.
Voice Recognition for Personalized User Interface Development
Voice recognition is being used to develop personalized user interfaces such as enhancing voice mail. By accurately recognizing the speaker, the system will be able to anticipate their needs and adapt its offerings based on the speaker’s preferences and requirements.
Recognizing the speaker makes it easier for businesses to provide a fully customized voice experience. As more and more voice-enabled devices are making their way into our homes, voice recognition will be a step in enhancing customer engagement and satisfaction.
Speaker recognition is identifying and authenticating a person’s identity based on voice characteristics. Voice recognition works on the principle that no two individuals can sound the same because of the differences in their larynx sizes, the shape of their voice tract, and others.
The reliability and accuracy of the voice or speech recognition system depend on the type of training, testing, and database used. If you have a winning idea for voice recognition software, reach out to Shaip for your database and training needs.
You can acquire an authentic, secure, and top-quality voice database that can be used to train or test your machine learning and natural language processing models.