You could first use ffmpeg to detect intervals of silence, like this
ffmpeg -i "input.mov" -af silencedetect=noise=-30dB:d=0.5 -f null - 2> vol.txt
This will produce console output with readings that look like this:
[silencedetect @ 00000000004b02c0] silence_start: -0.0306667
[silencedetect @ 00000000004b02c0] silence_end: 1.42767 | silence_duration: 1.45833
[silencedetect @ 00000000004b02c0] silence_start: 2.21583
[silencedetect @ 00000000004b02c0] silence_end: 2.7585 | silence_duration: 0.542667
[silencedetect @ 00000000004b02c0] silence_start: 3.1315
[silencedetect @ 00000000004b02c0] silence_end: 5.21833 | silence_duration: 2.08683
[silencedetect @ 00000000004b02c0] silence_start: 5.3895
[silencedetect @ 00000000004b02c0] silence_end: 7.84883 | silence_duration: 2.45933
[silencedetect @ 00000000004b02c0] silence_start: 8.05117
[silencedetect @ 00000000004b02c0] silence_end: 10.0953 | silence_duration: 2.04417
[silencedetect @ 00000000004b02c0] silence_start: 10.4798
[silencedetect @ 00000000004b02c0] silence_end: 12.4387 | silence_duration: 1.95883
[silencedetect @ 00000000004b02c0] silence_start: 12.6837
[silencedetect @ 00000000004b02c0] silence_end: 14.5572 | silence_duration: 1.8735
[silencedetect @ 00000000004b02c0] silence_start: 14.9843
[silencedetect @ 00000000004b02c0] silence_end: 16.5165 | silence_duration: 1.53217
You then generate commands to split from each silence end to the next silence start. You will probably want to add some handles of, say, 250 ms, so the audio will have a duration of 250 ms * 2 more.
ffmpeg -ss <silence_end - 0.25> -t <next_silence_start - silence_end + 2 * 0.25> -i input.mov word-N.mov
(I have skipped specifying audio/video parameters)
You’ll want to write a script to scrape the console log and generate a structured (maybe CSV) file with the timecodes – one pair on each line: silence_end and the next silence_start. And then another script to generate the commands with each pair of numbers.