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Audio or video files can be transcribed manually or automatically. [1] Transcriptionists can replay a recording several times in a transcription editor and type what they hear. By using transcription hot keys, the manual transcription can be accelerated, the sound filtered, equalized or have the tempo adjusted when the clarity is not great.
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [7] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [5]
OpenAI publicly launched the AI video generator Sora, offering new creative tools. Sora can create up to 20-second videos from text and modify existing videos by filling frames.
A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .
Otter.ai, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]
During inference, auto-regressive decoders use the token generated in the previous step as the input token. However, the vocabulary of target tokens is usually very large. So, at the beginning of the training phase, untrained models will pick the wrong token almost always; and subsequent steps would then have to work with wrong input tokens ...
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