Abstract: A real-time voice recognition method and a real-time voice recognition model training method are provided. The model training method includes: obtaining an audio feature sequence of sample voice data, the audio feature sequence comprising audio features of a plurality of audio frames of the sample voice data; inputting the audio feature sequence to an encoder of the real-time voice recognition model; chunking the audio feature sequence into a plurality of chunks by the encoder according to a mask matrix; encoding each of the chunks to obtain a hidden layer feature sequence of the sample voice data; decoding the hidden layer feature sequence by a decoder of the real-time voice recognition model to obtain a predicted recognition result for the sample voice data; and training the real-time voice recognition model based on the predicted recognition result and a real recognition result of the sample voice data.