Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be reordered and edited, as desired, to produce a finished video program for export.

Abstract: The disclosed technology is a system and computer-implemented method for assembling and editing a video program from spoken words or soundbites. The disclosed technology imports source audio/video clips and any of multiple formats. Spoken audio is transcribed into searchable text. The text transcript is synchronized to the video track by timecode markers. Each spoken word corresponds to a timecode marker, which in turn corresponds to a video frame or frames. Using word processing operations and text editing functions, a user selects video segments by selecting corresponding transcribed text segments. By selecting text and arranging that text, a corresponding video program is assembled. The selected video segments are assembled on a timeline display in any chosen order by the user. The sequence of video segments may be re-ordered and edited, as desired, to produce a finished video program for export.

Abstract: The technology disclosed relates to a machine learning based speech-to-text transcription intermediary which, from among multiple speech recognition engines, selects a speech recognition engine for accurately transcribing an audio channel based on sound and speech characteristics of the audio channel.

Abstract: The technology disclosed relates to data captured in streams from sensors. Streams often are edited, especially video and audio data streams. In particular, the technology disclosed facilitates identification of segments of an originally captured stream that find their way into a finally edited stream and identification of changed segments in the finally edited stream. Summary analysis on self-aligned meta-blocks of stream data is described, along with pushing at least some self-aligned meta-hashes into a blockchain network, applying an alignment and hashing procedure described in a smart contract.

Abstract: The technology disclosed relates to a machine learning based speech-to-text transcription intermediary which, from among multiple speech recognition engines, selects a speech recognition engine for accurately transcribing an audio channel based on sound and speech characteristics of the audio channel

Abstract: The technology disclosed relates to data captured in streams from sensors. Streams often are edited, especially video and audio data streams. In particular, the technology disclosed facilitates identification of segments of an originally captured stream that find their way into a finally edited stream and identification of changed segments in the finally edited stream. Summary analysis on self-aligned meta-blocks of stream data is described, along with pushing at least some self-aligned meta-hashes into a blockchain network, applying an alignment and hashing procedure described in a smart contract.

Abstract: The technology disclosed relates to data captured in streams from sensors. Streams often are edited, especially video and audio data streams. In particular, the technology disclosed facilitates identification of segments of an originally captured stream that find their way into a finally edited stream and identification of changed segments in the finally edited stream. Summary analysis on self-aligned meta-blocks of stream data is described, along with pushing at least some self-aligned meta-hashes into a blockchain network, applying an alignment and hashing procedure described in a smart contract.