The digital world is constantly evolving and providing more solutions to increase user convenience. Voice technology, in particular, has grown multifold in the past few years: over 41% of adult smartphone users report using voice search daily. In fact, 20% of all Google searches are made through the voice search feature.
The growing user preference for voice technology and an increasing number of voice based devices like Google Home have made voice testing more important than ever.
This article will help you understand the different types Voice & Artificial Intelligence Testing, the challenges they come with, the best practices for the process, and how Oprimes can help you conduct it effortlessly.
Types of Voice Based Device/ App Testing
Voice devices are a category of smart devices that are created to get complete tasks by listening and responding to voice conversations. The two prominent devices in this category are Amazon Echo and Google Home, which can be used for searching the web, ordering food, or even setting alarms. There are different types of voice enabled device testing that you can use to test these products. These include:
Unit testing is carried out by voice-based app developers and is done to ensure the code is working correctly in isolation. Unit testing focuses on ensuring that the code and logic are correct, preventing the need to hit the cloud or call external services.
The Quality Assurance teams carry out this type of testing. It is done to ensure that the whole system is working as it should, including the AI, code, and external parts. It involves a number of comprehensive tests and aims to imitate how real users would interact with the voice app.
Monitoring or Continuous Testing
This type of testing is done to check that the product, once released, works perfectly. It is carried out periodically to gauge the functioning of the voice-based app. Continuous testing should be easy to set up and give instant results when the app stops behaving properly.
Usability Performance Testing
Usability performance testing aims to identify problems with the software’s speech recognition and BLU behavior. It involves extensive testing of the interaction model and creating a baseline set of results that are used to improve the code.
The Challenges Of Voice Testing
Variation in Languages and Accents
The voice feature on apps is used by a diverse community of people who speak different languages and have unique accents. Therefore, voice enabled apps need to be able to comprehend and respond to this large group of users. When conducting Google Voice Testing or Alexa Voice Testing, face this large challenge since their product is used by people from across the world.
Different Age Groups
Similar to different languages, voice enabled products are used by people from varying age groups. Testers thus face the task of creating a great user experience for individuals of all ages.
High Volume of Datasets
Each simple voice command has many layers of complexities attached to it. While saying the “wake up” word to Alexa may seem like a basic task, it involves the device to comprehend and respond with the correct action. Similarly, smart home devices use a variety of voice based commands for tasks like turning on lights and switching off a power source, leading to a high volume of datasets in voice control testing.
Creating Datasets Based on Different Domains
Each domain requires a unique set of needs and core questions that the services revolve around. The requirement for a large number of datasets makes it tedious to manually generate these questions. Moreover, you also run the risk of not being able to cover all relevant questions and answers.
Best Practices for Voice Testing
Automated Voice Testing
Automated voice testing allows the tester to execute thousands of test cases without manual intervention. Automated voice testing makes it easy to identify common issues and track software improvements. AVT can be applied over the following use cases:
- Alexa apps testing (Amazon Echo device).
- Google Home apps testing.
- Voice-enabled websites and apps.
- Testing virtual assistants. This includes Siri on Apple products and Android voice testing for OK Google.
Crowdsourced Testing with Real Users
When conducting voice testing, it is essential to involve real users who speak different languages and dialects with varying accents. This will help uncover new problems with the application, which can then be transferred to automated testing.
Whether you’re looking for voice & artificial intelligence testing, voice chat testing, voice call testing, or a reliable voice quality testing solution, Oprimes is the right platform for you. We are India’s largest testing as a service (TaaS) provider and have a global curated community of professional testers and test-users which we have carefully built over the last five years. Our end-to-end testing solutions combine the power of automated and crowdsourced testing, helping you launch a successful, bug-free product.