自动字幕生成视频

Aditya Ramani, A. Rao, V. Vidya, V. B. Prasad
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引用次数: 7

摘要

字幕是从电影、电视节目、电脑游戏中的话语或评论的文本或剧本中获得的内容。在视频中的大部分情况下,声音都是一个关键的位置。目前,要在视频中加入字幕,我们必须从第三方下载并手动将其添加到我们选择的媒体播放器中。这带来了一些问题:我们试图转录的视频内容可能并不总是有现成的字幕,而且在我们消费它之前,甚至需要一个活跃的互联网连接才能搜索到这样的资源。我们的目标是通过在实时用例中对各种语音识别引擎进行比较分析来解决这些问题,例如,在离线环境中为媒体播放器上播放的视频生成字幕。在所比较的语音识别引擎中,DeepSpeech获得了较低的单词错误率(WER),为26%,但当我们考虑系统资源使用情况时,CMU Sphinx被证明是给定用例中更好的整体引擎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Subtitle Generation for Videos
Subtitles are content gotten from either a transcript or screenplay of the discourse or critique in movies, TV programs, computer games. In a lion's share of cases inside a video, the sound holds a critical spot. At present, to incorporate subtitles into the videos, we have to download them from a third-party source and manually add it to our media player of choice. This poses a few problems: The video content we are trying to transcribe may not always have subtitles readily available for it and an active internet connection would be required to even be able to search for such a resource before we can consume it. We aim to try to solve these problems by performing a comparative analysis of various speech recognition engines in a real-time use case, i.e. generating subtitles for a video being played on a media player in an offline environment. Among the speech recognition engines that were compared, DeepSpeech obtained the lower Word Error Rate (WER) of twenty-six percentage, but when we consider system resource usage as well, CMU Sphinx proves to be a better overall engine for the given use case.
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