In response to the current situation of low voice wake-up rate, low recognition rate, false wake-up, false recognition, and recognition errors in car voice interaction, which cannot be detected after execution, manual error correction verification is required. However, manual testing faces a large number of test cases and is prone to negligence. Based on the visual recognition technology of artificial intelligence, this article can automate testing and calculate the car voice wake-up rate, recognition rate, false wake-up, false recognition, and word error rate. Thus, problems can be identified and corrected in a timely manner, improving work efficiency and accuracy, thereby improving the accuracy of in vehicle speech recognition and the recognition rate of speech execution.
|