According to current estimates, individuals and companies publish over 1,200 new applications on the Apple App Store daily. Mobile apps offer opportunities for social networking, media sharing, banking, shopping and so much more. Software applications streamline and revolutionize many of the tasks we engage in regularly, and consumers have ready access to these tools via the mobile devices they use every day.
With so many mobile apps currently on the market, many software developers are looking for solutions to help their applications stand out. Voice-to-text technology is one solution that can help app developers offer more engaging, enjoyable experiences to all consumers. Also, software developers can use existing voice-to-text APIs to add captioning and transcription functionality to their applications and deliver more inclusive, robust user interfaces to their customer base. Let’s discuss some basics of using voice-to-text APIs in app development and explore how voice-to-text technology can enhance user experience.
Understanding Voice-To-Text API
First things first, what is an API? An API, or Application Programming Interface, is a set of rules and protocols that allows one software application to interact with another. APIs enable different software systems to communicate and share data seamlessly, so software developers can easily integrate existing functionalities into their new applications without programming everything from the ground up.
A voice-to-text API is one such interface. Voice-to-text APIs convert audio information to written text. This technology leans on a type of artificial intelligence — Automatic Speech Recognition technology or ASR. This advanced software solution uses language learning models to interpret human speech by combining bite-sized sounds or phonemes.
App developers can use voice-to-text APIs to add speech-to-text functions to their interfaces. For example, a developer could use a voice-to-text API to add captioning and transcription functions to their application. There are many potential uses for this type of speech-to-text technology, and using an existing voice-to-text API can help streamline integrating this functionality into a new application.
Use Cases of Voice-to-Text API
Today, professionals across nearly every industry embrace voice-to-text technology. Voice-to-text tools can streamline workflows, improve accessibility and boost brand discoverability. As a result, many software developers want to integrate this functionality into their applications.
Some app categories that stand to benefit from the use of voice-to-text APIs include:
- Note-Taking and Dictation Apps: With voice-to-text technology, users can dictate their notes verbally rather than manually typing them by hand.
- Voice Assistants: Virtual assistants like Siri, Alexa and Google Voice use voice-to-text APIs to interpret and respond to verbal commands.
- Accessibility Apps: Assistive technology applications use voice-to-text technology to represent speech as text via captions or transcripts for users who are Deaf or hard of hearing.
- Video Conferencing Apps: Apps like Zoom and Microsoft Teams can use a voice-to-text API to offer real-time speech to text conversion for live or post-meeting captioning transcription of virtual communications.
- Language Learning Apps: Language learning apps need to use some form of voice-to-text API to analyze a user’s pronunciation and provide constructive feedback.
- Translation Apps: With the help of voice-to-text APIs, translation applications execute and convert audio input from one language into a different language via text or audible read-out.
In addition to supporting these kinds of applications, voice-to-text APIs can integrate into nearly every type of app to enhance the overall accessibility of a user interface by making it possible for a user to control the app with just their voice. Additionally, voice-controlled apps are more inclusive of consumers with physical and mental disabilities and are more likely to comply with web accessibility guidelines.
Key Features and Functionality
Each voice-to-text API has its own set of features and functions. Some offer advanced functionality like multilingual voice recognition and cloud-based speech recognition, while others offer high customizability and open-source code options. When selecting the right voice-to-text API, developers should carefully consider which features and functions are must-haves for their projects and users.
However, the most basic functions of voice-to-text APIs are fairly similar across the board. Here is how the average voice-to-text API works in a mobile application:
- Step 1: The application receives audio input via a microphone or audio file.
- Step 2: The application sends the audio data to the API through HTTP requests.
- Step 3: The API uses ASR technology to analyze and convert the audio information to text.
- Step 4: The API returns the converted text to the application, which is then provided to the end-user for the intended purpose.
Benefits and Advantages
Automatic speech recognition technology is an incredibly complicated and advanced artificial intelligence software. Attempting to incorporate voice-to-text functionality into an application from scratch is highly time-consuming and costly for the average software developer. That’s why developers typically prefer using an existing API to enhance their applications with voice-to-text capabilities.
In addition to enhancing accessibility with voice to text technology, software developers may wish to incorporate these solutions to improve their app’s overall user experience. A reliable voice-to-text API can help developers add a wide range of additional features and functions to their applications and help them create more valuable, versatile products.
Potential Challenges in Integration and Implementation
While voice-to-text APIs can undoubtedly enhance the average mobile application, there are a few things developers should keep in mind when considering using an existing API to add voice-to-text functionality to their apps. First and foremost, it is essential to understand that most major voice to text API providers like Google Cloud, Amazon Transcribe and IBM Watson rely on artificial intelligence to convert audio to text.
Computers can do remarkable things, and ASR software is constantly evolving. However, the many subtle nuances within human speech can make it difficult for a computer to accurately interpret or represent audio input in the presence of confounding variables 100% of the time. For example, suppose a user tries to use a dictation application in a noisy environment. In that case, the voice-to-text API may struggle to filter out background noise to accurately transcribe what the user is saying. Similarly, software APIs tend to encounter difficulty when an audio sample features multiple speakers, crosstalk, poor audio quality or unique dialects.
There are plenty of opportunities for integration of voice-to-text in businesses and entertainment settings. However, some industries require special considerations when employing any software API. For instance, there is certainly a need for voice-to-text in healthcare and legal sectors. Unfortunately, not every software solution is up to the task of meeting the stringent data security and confidentiality requirements of these industries. If a developer is working on an application for use in either of these industries, they will want to look very closely at the security protocols of any voice-to-text APIs they are considering to ensure they meet all industry-specific requirements.
Partners with Voice-to-Text APIs
Voice-to-text APIs can make it faster, easier and more convenient for software developers to add speech-to-text functions to their applications. This type of software can make captioning and transcription tools more readily available to consumers who need them while offering more engaging user experiences to app users across the board. If you’re a developer, creator or business leader looking to support your mobile applications with voice transcription capabilities, however, it might be worth it for you to consider partnering with a trusted provider like Verbit.
Verbit understands the benefits and limitations of AI and machine learning in voice transcription. That’s why they combine their automated transcription services with input from professionally trained human transcribers to produce more user-friendly, accurate captions and transcripts. Verbit’s transcription platform integrates seamlessly with popular media hosting and communication platforms and applications, so software developers can easily integrate voice-to-text technology into their projects without settling for sub-par accuracy rates or clunky UX.
If you’re interested in learning more about future trends in voice to text technology or want more information about Verbit’s state-of-the-art assistive technology solutions, reach out today to speak to a member of our team.