Hey, everyone.
And welcome back.
Now, in today's video, we are going to discuss about Amazon transcribe.
Now, at a high level overview, transcribe is an automatic speech recognition service that uses machine
learning to convert audio to text.
So at a high level overview, it is a speech to text converter.
So whatever audio file, let's say you have an audio file of your meeting and you want to quickly get
the text associated with it so you can supply that audio file to the transcribe service and transcribe
it automatically convert them to text.
So that's the high level overview.
Let's go ahead and try it out.
Now for today's demo, I have a simple transcribe based recording which I just recorded and we'll go
ahead and supply to transcribe and we'll see if it is able to convert it to appropriate text.
Now before we do that, let me play it out so that we understand what is the words that are being used
here.
Hey, everyone, and welcome back.
This audio is to test how well the speech to text converter box.
Now let's go ahead and try it out.
So let's quickly create a new job.
I'll say demo job within the language is English.
And what you need to do over here is you'll have to specify the location of the bucket where your recording
is present.
Now, in my case, I already have uploaded a recording over your two or three bucket and will be supplying
the three bucket details over here.
So let's quickly get the UI of our file.
And let me add it to make sure it is in the same region, both the bucket as well as the service.
Once.
Then you also have option to have a subtitle file format.
So this is quite useful if you require subtitles for your video files.
So once then you can click on next.
Now audio setting is quite powerful and this makes transcribe a great service.
So not only it is a simple speech to text converter, this is definitely there at the core, but along
with that it provides very powerful results related to content removal.
In case if there are any PII data, for example in the audio recording, it can go ahead and redact
the PII data.
Along with this, you can also select what are the data that you might want to redact, maybe credit
card, CVB, maybe the PIN bank account number and so on.
So this makes transcribe a really powerful service.
Once you have configured the appropriate audio settings, we'll keep it simple.
We'll create a job.
So at this stage the status is in progress.
So let's quickly wait for a moment here.
Now, at this stage they do not have a refresh button in the console itself.
So what you can do, maybe you can refresh the page, maybe the refresh button at a console level will
appear at a later stage.
So once you refresh the page, the status is now completed.
So now if I quickly open this up.
And if you look into the text, it states.
Hi, everyone, and welcome back.
This audio is to test how well the speech to text converter works.
Now the last word works is converted here to and water box.
So again, it really depends upon your accent and the quality of audio recording for the accurate results.
Now, one more thing I wanted to show you is that it also goes ahead and it can perform real time.
Transcription.
So in case if you stream some data, it can convert this to real time as well.
And this is quite good.
So let's trim it.
I'll click on aloe.
Hi, everyone, and welcome back.
Let's see how well the speech to text converter works.
I'll stop screaming.
And this time, you see, it provided quite good results.
All right.
So I hope with this you understood the basics of transcribed service.
Now, within the transcribed they have one sub feature or you can say maybe sub service associated with
call analytics.
So this call analytics features allows organizations to gain insights into the customer agent interaction.
And for example, let's say you have a call center where there are hundreds of calls that are happening
every day.
So based on the recordings of the call, transcribed call analytics can go ahead and provide you with
various information.
For example, it can provide you with the characteristics of call like the talk time, non talk time
speaker, loudness, interruptions, speed and others.
It can also give you information related to the speaker sentiment for each call at various points of
call, whether it is positive or negative and so on.
So at this stage you will see that Amazon transcribe is divided into the transcribe, which is the code
and transcribe call analytics.
So these are two features at this stage.
You also have the Amazon transcribe medical for medical related data.
Now generally at a later stage you might see us separating out this service altogether.
For example, when I type Amazon transcribe here, there is only one service, but at a later stage
it is observed that they generally separate out the service.
So you might see transcribe here, you might see transcribed call analytics here and so on.
So this is one thing that you need to note.
So that's the high level overview and with this will conclude today's video.