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#Automated testing
  1. arXiv Game AI36

    Study proposes ResNet-BiLSTM for multi-label perceptual bug detection from gameplay footage

    The study proposes a ResNet-BiLSTM model that performs multi-label perceptual bug detection on gameplay footage, achieving an F1 score of 85.78% on a benchmark dataset, and compares it with video classification models including Inflated 3D ConvNet and 3D ResNet.

    Why it matters: The paper reports an F1 of 85.78% for ResNet-BiLSTM and compares it with video classification models such as Inflated 3D ConvNet on the same task.

  1. Unity67

    Unity demos prototyping a UI Toolkit main menu from concept art with the CLI and an AI agent

    Unity has released a tutorial video showing how an AI agent, working through the Unity CLI and starting from concept art and a short brief, can build a usable main menu interface directly inside the Unity editor.

    Why it matters: The original walks through the full agent workflow from concept art to a runnable main menu, and its approach of command-line testing with screenshot feedback can be carried over to your own projects.

  1. Inworld AI Blog56

    Inworld AI open-sources the TTS Open Evaluation Toolkit

    Inworld AI has open-sourced the TTS Open Evaluation Toolkit, a customizable TTS evaluation framework for sampling TTS systems, evaluating audio offline and generating comparable reports.

    Why it matters: The post explains why the same TTS model can produce different WER in different teams' hands, and covers how to run this evaluation tool and its first set of metrics.

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