Abstract: A respective set of features, including emotion-related features, are extracted from segments of a video for which a preview is to be generated. A subset of the segments is chosen using the features and filtering criteria including at least one emotion-based filtering criterion. Respective weighted preview-suitability scores are assigned to the segments of the subset using at least a metric of similarity between individual segments and a plot summary of the video. The scores are used to select and combine segments to form a preview for the video.

Abstract: An automated solution to determine suitable time ranges or timestamps for captions is described. In one example, a content file includes subtitle data with captions for display over respective timeframes of video. Audio data is extracted from the video, and the audio data is compared against a sound threshold to identify auditory timeframes in which sound is above the threshold. The subtitle data is also parsed to identify subtitle-free timeframes in the video. A series of candidate time ranges is then identified based on overlapping ranges of the auditory timeframes and the subtitle-free timeframes. In some cases, one or more of the candidate time ranges can be merged together or omitted, and a final series of time ranges or timestamps for captions is obtained. The time ranges or timestamps can be used to add additional non-verbal and contextual captions and indicators, for example, or for other purposes.

Abstract: Disclosed are various embodiments for evaluating the accuracy of a translation of a source text. Word embeddings from a first language and a second language are aligned in a shared vector space. Word pairs from the sourced text and translated text are then identified. Subsequently, similarity scores between respective word embeddings for the words in the word pair are calculated. Word pairs are then selected based on the similarity scores. The accuracy of the translation is then evaluated based at least in part on the selected word pairs.

Abstract: A vent hole cleaning system is disclosed. The cleaning system is comprised of a housing containing a work table and a support column. The system further comprises a robotic arm mounted on the support column. Further, a subsystem is mounted at an end, opposite to the support column, of the robotic arm. The subsystem may comprise a scanner configured to generate a contour profile of a mold. Further, a vision system may be mounted on the subsystem. The vision system may be communicably connected to the scanner. Further, the system may comprise a cleaning head communicably connected to the vision system and the scanner to enable precision positioning on the mold.

Abstract: A vent hole cleaning system is disclosed. The cleaning system is comprised of a housing containing a work table and a support column. The system further comprises a robotic arm mounted on the support column. Further, a subsystem is mounted at an end, opposite to the support column, of the robotic arm. The subsystem may comprise a scanner configured to generate a contour profile of a mold. Further, a vision system may be mounted on the subsystem. The vision system may be communicably connected to the scanner. Further, the system may comprise a cleaning head communicably connected to the vision system and the scanner to enable precision positioning on the mold.