60 lines
No EOL
1.5 KiB
Markdown
60 lines
No EOL
1.5 KiB
Markdown
########### WHAT IS PRODUCED: ###########
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SPEAKER 1 0:00:04 - 0:00:06
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Transcription technology has improved so much in the past
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SPEAKER 1 0:00:07 - 0:00:12
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years. Have you noticed how accurate real-time speech detects is now?
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SPEAKER 2 0:00:12 - 0:00:12
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Absolutely
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SPEAKER 1 0:00:13 - 0:00:13
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.
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SPEAKER 2 0:00:14 - 0:00:14
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I
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SPEAKER 1 0:00:14 - 0:00:17
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use it all the time for taking notes during meetings.
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SPEAKER 2 0:00:17 - 0:00:17
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It
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SPEAKER 1 0:00:17 - 0:00:22
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's amazing how it can recognize different speakers, and even add punctuation.
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SPEAKER 2 0:00:22 - 0:00:22
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Yeah
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SPEAKER 1 0:00:23 - 0:00:26
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, but sometimes noise can still cause mistakes.
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SPEAKER 3 0:00:26 - 0:00:27
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Does
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SPEAKER 1 0:00:27 - 0:00:28
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this system handle that
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SPEAKER 1 0:00:29 - 0:00:29
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?
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SPEAKER 3 0:00:29 - 0:00:29
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It
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SPEAKER 1 0:00:29 - 0:00:33
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does a pretty good job filtering noise, especially with models that use voice activity
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########### WHAT SHOULD BE PRODUCED: ###########
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SPEAKER 1 0:00:04 - 0:00:12
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Transcription technology has improved so much in the past years. Have you noticed how accurate real-time speech detects is now?
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SPEAKER 2 0:00:12 - 0:00:22
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Absolutely. I use it all the time for taking notes during meetings. It's amazing how it can recognize different speakers, and even add punctuation.
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SPEAKER 3 0:00:22 - 0:00:28
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Yeah, but sometimes noise can still cause mistakes. Does this system handle that well?
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SPEAKER 1 0:00:29 - 0:00:29
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It does a pretty good job filtering noise, especially with models that use voice activity |