A wakeup word detection method and apparatus (700) employing artificial intelligence, a device, and a storage medium. The method comprises: using a pre-configured pronunciation dictionary to construct at least one syllable combination sequence for user-defined wakeup word text inputted by a user by means of a user interface; acquiring speech data to be subjected to recognition, and extracting a speech feature of each speech frame in the speech data (101); inputting the speech features into a pre-constructed deep neural network model, and outputting posterior probability vectors of the speech features with respect to a syllable identifier, wherein the deep neural network model comprises the same number of syllable output units as the number of syllables in the pre-constructed pronunciation dictionary (103); and determining a target probability vector from the posterior probability vectors according to the syllable combination sequence, calculating a confidence according to the target probability vector, and when the confidence is greater than or equal to a threshold, determining that the speech frame comprises the wakeup word text, wherein the syllable combination sequence is constructed according to the input wakeup word text (105).
WAKEUP WORD DETECTION METHOD AND APPARATUS EMPLOYING ARTIFICIAL INTELLIGENCE, DEVICE, AND MEDIUM