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########### WHAT IS PRODUCED: ###########
SPEAKER 1 0:00:04 - 0:00:06 Transcription technology has improved so much in the past
SPEAKER 1 0:00:07 - 0:00:12 years. Have you noticed how accurate real-time speech detects is now?
SPEAKER 2 0:00:12 - 0:00:12 Absolutely
SPEAKER 1 0:00:13 - 0:00:13 .
SPEAKER 2 0:00:14 - 0:00:14 I
SPEAKER 1 0:00:14 - 0:00:17 use it all the time for taking notes during meetings.
SPEAKER 2 0:00:17 - 0:00:17 It
SPEAKER 1 0:00:17 - 0:00:22 's amazing how it can recognize different speakers, and even add punctuation.
SPEAKER 2 0:00:22 - 0:00:22 Yeah
SPEAKER 1 0:00:23 - 0:00:26 , but sometimes noise can still cause mistakes.
SPEAKER 3 0:00:26 - 0:00:27 Does
SPEAKER 1 0:00:27 - 0:00:28 this system handle that
SPEAKER 1 0:00:29 - 0:00:29 ?
SPEAKER 3 0:00:29 - 0:00:29 It
SPEAKER 1 0:00:29 - 0:00:33 does a pretty good job filtering noise, especially with models that use voice activity
########### WHAT SHOULD BE PRODUCED: ###########
SPEAKER 1 0:00:04 - 0:00:12 Transcription technology has improved so much in the past years. Have you noticed how accurate real-time speech detects is now?
SPEAKER 2 0:00:12 - 0:00:22 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.
SPEAKER 3 0:00:22 - 0:00:28 Yeah, but sometimes noise can still cause mistakes. Does this system handle that well?
SPEAKER 1 0:00:29 - 0:00:29 It does a pretty good job filtering noise, especially with models that use voice activity