########### 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