So now let's talk about Amazon Transcribe.
So Transcribe, as the name indicates,
is used to convert speech into text.
So I will speak into my microphone
and this will be the audiogram I get out of it.
And then, thanks to Transcribe, it's going to analyze
the text and say, "Hello, my name is Stephane.
"I hope you're enjoying the course!"
Okay, so how does it do it?
Well, it uses a deep learning process called
automatic speak recognition, ASR, to convert the speech
to text quickly and accurately.
And what if there is some PII data in the audio?
So PII means personally identifiable information.
For example, someone's age and so on.
Then we can use the redaction feature
from within Amazon Transcribe.
And so thanks to it, we can remove automatically
any PII data using redaction.
So it will say, "Hello, my name is Stephane.
"My age is," and then blank
because we've removed that information.
So the use cases for Amazon Transcribe
is to transcribe customer service calls
or to automate closed captioning and subtitling
and to generate metadata for media assets
in order to create a fully searchable archive.
If you wanted, you could try out Transcribe directly
from the AWS console.
You can launch Transcribe and then you would,
for example, start streaming.
So we'd say, "Hello, I really like this course,"
then stop streaming and then you would get
the transcription outputs.
So this is a good way to see how Transcribe would work.
Have fun and I will see you in the next lecture.