Voice recognition apps are one of the many fundamental improvements brought about by the rise of artificial intelligence in the digital commercial world. Voice recognition technology has taken over a huge portion of the global market, whether we're talking about video streaming apps, healthcare apps, or even search engines like Google. But the question is how to make a voice recognition app, and how does it benefit your company and customers? Let's have a look at it more closely!
What is a Voice Recognition App?
Voice recognition is a smart technology that converts human words, sounds, or phrases into a machine-understandable format and generates an output. The vocal signals are first translated to electric signals, then to codes, which the application analyses. Voice recognition app development assures not only an interactive and user-friendly search, but also makes other tasks such as listening to music, viewing movies, and phoning easier for your users. Better sales, earnings, and brand value in the market are all associated with satisfied customers. Not to mention the benefits of free advertising combined with a great user experience, which will help you develop your business.
Types of voice recognition app
There are currently two approaches to build voice recognition app:
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Speaker-Dependent Voice Recognition Apps
The first method, known as template matching, results in speaker-dependent systems being delivered. Such devices can only detect one person's voice and require prior training. Only particular sound patterns are recognised by the system, which the user teaches the app by repeating phrases or orders a few times. The algorithm then calculates the average of the repeated samples of pronounced sentences, which serves as a template. Following the system's "training" phase, it can recognise the meaning of statements that only fit into established templates.
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Speaker-Independent Voice Recognition Apps
The feature analysis approach is the second method for creating voice recognizers. During the creation of such applications, speaker-independent applications are created. These systems have the advantage of being able to detect the voice of many speakers without requiring any prior training. The voice input is processed using "linear predictive coding (LPC) or Fourier transformations," and the system then compares the expected voice input to the actual phrase said by the user. This method has one more advantage: unlike speaker-dependent systems, independent systems can deal with differences in accent, pitch, loudness, speed, and other factors that vary from person to person.
Voice Recognition Apps: Market Stats
Voice recognition technology, such as Alexa, Siri, or Google Assistant, has come a long way to providing customers with convenience and efficiency while also increasing earnings and brand value for businesses. At least, that's what the numbers say!
- The market for voice recognition technology is estimated to reach $27.16 billion by 2025, according to Statista.
- People were already using 4.2 billion digital voice assistants in 2020. By the year 2024, this figure is predicted to reach 8.2 billion!
- Voice searches on mobile phones have become a part of nearly 72 percent of people's everyday routines.
- Voice searches are three times more likely to be used by mobile users around the world than regular searches.
- At least once a week, 31% of smartphone users around the world perform voice searches.
The Importance of a voice recognition app
A wide range of potential consumers will benefit greatly from voice recognition. Obviously, anyone with a physical impairment who finds typing difficult, uncomfortable, or impossible will benefit greatly from it. It can also help to lower the chance of developing a repetitive strain injury (RSI) or to better treat any upper limb problem.
People with dyslexia who have trouble spelling and/or organizing phrases correctly can tremendously benefit from voice recognition apps.
Voice recognition can assist make mobile working easier in general, as well as provide possible productivity benefits to those who aren't great at typing. In fact, most people can speak far faster than they can write accurately, and 'hands-free' computing allows for more multitasking.
Voice Recognition App Development Process:
Choose The Type of Voice Recognition App
The first thing you should think about is what kind of Voice recognition app you want to make. There are two major sorts of voice recognition apps that we've discussed previously.
Focus on APIs and Core Technologies
After you've decided on the type of speech recognition app that best suits your needs, the next step is to decide on the tech stack for your voice recognition app development. Coding using the correct resources and tech stack makes your work a lot easier and more effective than beginning from the ground up, especially when you're just getting started.
Most people, however, lack a clear understanding of the most trustworthy and up-to-date tech stack and API. That's when the specialists come in! So, to assist you with voice recognition app development, we've listed some popular and effective tech stacks and APIs that you might use.
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Programming Languages
To begin developing a speech recognition app, you must first choose an efficient programming language that will serve as the foundation for your app. A voice recognition programme might use a variety of languages, but Python is the most popular choice.
The reason for this is that Python has a low level of complexity and is extremely user-friendly, especially for those who are new to programming. Aside from that, it comes with a slew of APIs and libraries that make developing speech recognition apps a breeze.
For web applications, you can utilize PHP or JavaScript in addition to Python. C# is also used in voice recognition app development.
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APIs
Depending on the features you want to integrate, you may choose from a variety of APIs for your voice recognition app development. Some APIs, on the other hand, are required to make your speech recognition app a market success.
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Google Speech API |
Google's AI-powered API that converts speech into text in real time. |
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Bing Speech API |
This API translates your speech to text, then alters it before converting it back to speech. |
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Amazon Alexa |
Integrates Alexa with your devices so that customers can obtain their answers quickly and effortlessly in an audio format. |
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Speech-to-Text API |
Convert audio to text and assist users in searching for information, as well as playing videos and music on the app. |
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SpeechAPI |
This API eliminates background disturbances for the user, allowing the app to analyze audio segments more effectively. |
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Rev.AI API |
It translates audio to text, including capitalization, punctuation, and conversion from live streaming videos. |
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ReadSpeaker API |
A one-of-a-kind API that turns the app's text or output into audio format for consumers. |
All of these APIs make it simple to turn a user's text into speech or vice versa. Aside from that, there are a number of third-party APIs such as Nuance's Automatic Speech Recognition, Speech 2 Topics, and Wit API that can help your bespoke voice recognition app operate even better.
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Libraries
Libraries, like APIs, play an important role in the development of efficient and customized voice-recognition apps. So, we've listed some open-source libraries that are quick, accurate, and free for your unique voice recognition app below!
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CMU Sphinx |
This library is designed in Java, but you may use it to create a sophisticated voice recognition application using any other programming language, such as Python or C#. |
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PyTorch |
PyTorch is yet another excellent Python-based package for converting speech to text for use in voice recognition applications. |
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HTK |
This library, which is owned by Microsoft, is used in statistical analysis modeling techniques that can analyze voice, characters, and convert speech to text. |
Other libraries, including these, can certainly be used depending on your project's needs and adaptations.
Features to Consider while Developing a Voice Recognition App
Aside from the technology stack and libraries, features are also important in determining the breadth of your speech recognition app. If you're making a speech recognition search app, for example, you might need to incorporate picture and manual search options in addition to voice-based searches. Apart from that, noise-canceling APIs and other programming platforms are included in smartphone voice assistants.
Similarly, if you want to create a virtual assistant app, AI and machine learning techniques, as well as natural language processing, would suffice. In that scenario, you may need to implement additional features such as playing music from the tap, calling from voice commands, turning off the fan, and so on. As a result, knowing what type of speech recognition app you want will assist you choose the features.
Selecting a Team of voice recognition app Developers
After you've completed your research and validation, you'll need a dedicated team of tech-savvy developers and testers to assist you in developing your custom speech recognition app at the most cost-effective prices and in the shortest amount of time possible.
Examples of resources include, but are not limited to:
- Project Manager
- Front-end Developers
- Backend Developer
- Tester
- API Developers
- UI/UX Designer
Finding the right tech-savvy and experienced engineers for your app development, on the other hand, can be a difficult endeavor, especially for those who are just getting started. So, what's the best course of action?
Some Other Things to Keep in Mind During Voice Recognition App Development
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Analyze Your Project Idea
Before beginning any project, the first and most important step is to analyse and validate your concept with professionals. You must have a thorough understanding of the underlying issue and the solution that your app will provide.
Aside from that, you should get professional approval for your app concept. All of the features, tech stack, and designs must be trustworthy and trendy, and who better to assist you than an expert?
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Determine Whatever Technical Skills Are Required
You may need to add some technical features to your project depending on the type of speech recognition app you're creating. Because voice recognition is an application of artificial intelligence, all of these technological skills would incorporate one or more characteristics of AI. As a result, technology such as machine learning techniques, natural language processing, acoustic modeling for voice recognition, and an autonomous speech recognition system would be extremely useful.
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UI/UX
Aside from the tech stack and advanced features, the UI/UX of your voice recognition app can have an impact on its development. The user interface, or screen that your clients will view, is referred to as UI, but the experience that your app will provide is referred to as UX.
Read More: Other Article Reference
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Testing
Last but not least, we offer testing services, which are the most important component of developing a speech recognition app. Many firms ignore testing in order to save time and money on their app development. As a result, they encounter bugs and faults in their app, tarnishing their brand's image in the market. You certainly don't want this to happen to your voice recognition app!
How much does it cost to develop voice recognition App
The cost of developing and designing voice recognition apps has been the subject of numerous studies.
A number of factors influence the price, including:
- Complexity
- Platforms
- Functionalities and features
- A mobile app development company's development rates
These are the factors that increase the cost of developing a mobile app. You can acquire a thorough quote from a reliable mobile app development business or contact us directly if you prefer. We collaborate with businesses and clients all over the world. IT Kamtech is considered as one of the most important mobile app development firms in the business.
Some Voice Recognition App Reference
1. Speechnotes
The punctuation keyboard is undoubtedly Speechnotes' best feature. Many people find dictating punctuation marks difficult (for example, you typically have to say "Hi Mum comma please pick up the kids").
The punctuation keyboard includes on-screen keys for the most frequently used punctuation marks, allowing you to dictate more quickly and naturally. Emojis and symbols are also available. Bluetooth compatibility, a home screen widget for fast dictation, and offline note-taking are among the other essential features. The app also allows you to record indefinitely. That means, unlike many other dictation apps, you can take long pauses between sentences to collect your thoughts while the programme continues to listen.
2. Voice Notes
Speechnotes was created with extensive dictations in mind, such as lectures and essays. Voice Notes, on the other hand, takes a different approach, focused on capturing quick notes on the go. On the app, there are two primary ways to keep track of your notes. You can either save the audio file to listen to later or utilize the speech-to-text feature to see a transcribed version of your notes on the screen.
3. SpeechTexter
SpeechTexter is an Android appthat converts speech to text and works both online and offline. Because the app uses Google's database, you'll need to download the relevant language packs if you wish to use the offline mode.
You may use SpeechTexter to create SMS messages, emails, and tweets in addition to basic dictation and speech-to-text. A custom lexicon is included in the app, and adding personal information such as phone numbers and addresses is simple.
Conclusion
In this article, we covered the entire process of how to make a voice recognition app as well as some related topics. When it comes to custom app creation, we at IT Kamtech have an unending list of clients.
So, don't delay and take advantage of our free consultation to get started on developing a result-oriented and user-friendly voice recognition app.
Frequently Asked Questions
Which programming language is best for voice recognition?
The object-oriented programming language Java is in high demand. Because of its wide characteristics, it is in high demand. Java creates a Java Voice API for creating speech recognition techniques.
Why Use a Voice Recognition App ?
Many people unconsciously use speech recognition apps on a daily basis. A speech recognition app is used by every virtual assistant incorporated into a smartphone to listen to a user's voice requests. This demonstrates the importance of voice recognition apps in our daily lives.
How does a voice recognition algorithm work?
Something is still missing from the data, even after it has been digitized. Three sound elements are required for speech recognition. Its frequency, intensity, and duration of creation. As a result, the graph is converted into a spectrogram using a complicated voice recognition process known as the Fast Fourier Transform.
