CrossASR: Efficient differential testing of automatic speech recognition via text-to-speech

• المؤلفون الرئيسيون: ASYROFI, Muhammad Hilmi, Ferdian, Thung, LO, David, JIANG, Lingxiao
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2020
• الموضوعات: Automatic Speech Recognition; Differential Testing; Failure Probability Predictor; Test Case Generation; Text-to-Speech; Software Engineering
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/5536; https://ink.library.smu.edu.sg/context/sis_research/article/6539/viewcontent/icsme20crossASR.pdf
• المؤسسة: Singapore Management University

Automatic speech recognition (ASR) systems are ubiquitous parts of modern life. It can be found in our smartphones, desktops, and smart home systems. To ensure its correctness in recognizing speeches, ASR needs to be tested. Testing ASR requires test cases in the form of audio files and their transc...