Automating Audio and Video Quality Testing: An Overview


This document serves as an introduction to automating audio and video quality testing. Through automation methods, organizations can enhance the evaluation process and optimize the performance of their audio and video applications. In this introduction, we will explore the advantages of automated testing, the limitations of manual testing, and the significance of delivering high-quality audio and video experiences to users.

Benefits of Automating Audio and Video Quality Testing

Automating audio and video quality testing offers several advantages over manual testing methods. By embracing automation, organizations can:

Enhanced Testing Efficiency:

  • Automation methods allow for a significant increase in tests conducted, enabling thorough audio and video quality evaluation.
  • Automated testing tools can execute many tests efficiently, saving time and resources compared to manual testing.

Consistent and Reliable Results:

  • Automation ensures consistent testing procedures, eliminating variations that may arise from human error during manual testing.
  • Automated systems deliver reliable and reproducible results by adhering to predefined testing protocols.

Improved Test Coverage:

  • Automation facilitates the execution of a broad range of tests, covering various scenarios and use cases for audio and video applications.
  • With automation, it becomes feasible to test the performance of applications across different devices, platforms, and network conditions, ensuring comprehensive evaluation.

Continuous Testing Capability:

  • Unlike manual testing, automation allows for continuous testing without time limitations. Tests can be executed around the clock, providing extensive data for analysis.
  • Automated systems can execute tests consistently, helping organizations identify and resolve issues promptly.

Resource Optimization:

  • Automation reduces the dependency on manual testers, freeing up valuable human resources for more complex and strategic tasks.
  • Organizations can allocate their resources effectively and achieve higher productivity by minimizing the need for manual intervention.

Scalability and Flexibility:

  • Organizations can easily scale their automated testing frameworks to accommodate larger volumes of tests, making them suitable for evolving application requirements.
  • With the ability to adapt and integrate with different platforms and tools, automation offers flexibility in testing diverse audio and video applications.

Objective Evaluation:

  • Automated testing employs objective evaluation methods, relying on predefined metrics and algorithms to assess audio and video quality.
  • This objectivity eliminates subjectivity that may be present in manual testing and provides organizations with data-driven insights.

Early Issue Detection:

  • Automated testing allows for quick identification of audio and video quality issues, enabling organizations to address them early in the development lifecycle.
  • Organizations can avoid costly rework and enhance the overall user experience by detecting issues early.

Challenges of Manual Testing

While manual testing is still valuable, it has limitations that make automation a preferred choice. Manual testing:

  1. Relies on Limited Resources: Manual testing is constrained by human resources, making it difficult to conduct tests continuously or scale testing efforts.
  2. Requires Intensive Focus: Manual testers must pay close attention to ensure accurate test execution, including monitoring network connections and timely media capture. This aspect demands intense concentration and increases the risk of errors.
  3. Imposes Time Constraints: Manual testers cannot perform tests around the clock, resulting in longer test cycles and delayed issue identification.

Automated Audio and Video Quality Testing

To automate audio and video quality testing effectively, organizations employ various strategies:

  1. Test Setup: Establishing the correct test environment is crucial to simulate real user scenarios accurately. This step includes choosing appropriate evaluation algorithms, network-limited tests, and utilizing suitable tools for testing different platforms.
  2. Capturing Quality Metrics: HeadSpin uses high-resolution cameras to capture video content to evaluate its quality objectively continuously. Simultaneously, audio from the device under test is captured using microphones and Bluetooth (if applicable), ensuring quality assurance for audio & video and enabling detailed audio analysis.
  3. Analyzing Video Quality: Automation enables the assessment of video quality parameters such as blurriness, blockiness, brightness, colorfulness, contrast, exposure, flickering, and freezing. This comprehensive analysis provides insights into the application’s visual performance.
  4. Streaming Performance Evaluation: Automated tests assess critical aspects of streaming performance, including video frame rate drops, loading/buffering time, and overall stability, ensuring a seamless user experience.

Our (HeadSpin) Automated Testing Process

To automate audio and video quality testing effectively, we have devised a meticulous process that ensures accurate evaluation and reliable results. Our process involves the following steps:

Capturing Quality of Experience (QoE) and Streaming Performance KPIs:

  • We employ high-resolution cameras to capture video content continuously, allowing us to assess its quality objectively. Additionally, we capture audio from the device under test using microphones and Bluetooth (if enabled), which can be further analyzed using our audio match analysis capabilities.

Assessing Video Application Performance:

  • Our automated testing covers various video applications, including media, entertainment, gaming, and video conferencing. This comprehensive approach enables us to evaluate the performance of these applications under multiple scenarios and identify potential weaknesses.

Testing on Different Devices and Platforms:

  • We conduct tests on over-the-top (OTT) media devices to account for the diversity in devices and platforms. This method ensures that our evaluation encompasses different screen sizes, aspect ratios, and operating systems, providing a holistic understanding of the application’s performance.

Evaluating DRM-Protected Content:

  • We test the application’s capability to handle digital rights management (DRM)-protected content, assessing its compatibility, security, and overall performance in safeguarding intellectual property.

Testing Voice Activation and Speaker-Based Use Cases:

  • We specifically evaluate voice activation and speaker-based use cases, ensuring that the application’s audio features meet the highest quality standards.

Advanced Analysis and Perceptual Quality Metrics

In addition to capturing performance data, we employ advanced video and audio analysis capabilities to assess perceptual quality objectively. Our comprehensive evaluation includes the following:

  • Analyzing video quality parameters such as blurriness, blockiness, brightness, colorfulness, contrast, exposure, flickering, freezing, and more.
  • Measuring video frame rate drops and loading/buffering time to evaluate the application’s streaming performance.
  • Employing reference-free video Mean Opinion Score (MOS) to quantify the subjective perception of video content. This AI-based model is trained on thousands of subjective quality scores, accurately assessing perceptual video quality.


Automated audio and video quality testing is crucial in meeting the rising user expectations for high-quality video conferencing experiences.

By adhering to rigorous testing procedures, leveraging advanced analysis capabilities, employing automation tools, and letting users test with our audio-visual platform, we ensure that we thoroughly test the performance of video conferencing applications and promptly identify and resolve any issues.

Jasper is a professional business and startup blogger that writes for a variety of leading sites. He loves content partnerships with advertisement agencies.