Abstract: A system and method for multimodal video segmentation in a multi-speaker scenario are provided. A transcript of a video with a plurality of speakers is segmented into a plurality of sentences. Speaker change information is detected between each two adjacent sentences of the plurality of sentences based on at least one of audio content or visual content of the video. The video is segmented into a plurality of video clips based on the transcript of the video and the speaker change information.

Abstract: An English pronunciation assessment method includes: receiving an audio file including an English speech and a text transcript corresponding to the English speech; inputting audio signal to one or more acoustic models to obtain phonetic information of each phone in each word, wherein the one or more acoustic models are trained with speeches spoken by native speakers and further with speeches spoken by non-native speakers without labeling out mispronunciations, such that a pronunciation error is detected more accurately based on the obtained phonetic information; extracting time series features of each word; inputting the extracted time series features of each word, the obtained phonetic information of each phone in each word, and the audio signal included in the audio file to a lexical stress model to obtain misplaced lexical stress in each of words in the English speech with different number of syllables without expanding short words to cause input approximation.