Speech to Text using AWS Transcribe

Cloud-based platform Amazon Web Services (AWS) offers users on-demand cloud computing services. A few of the resources provided by AWS are cloud computing services, networking, data storage facilities, different types of APIs and plugins, and many more. The blog will be laser-focused on the Amazon Web Service Transcribe using Python and its alternatives in the market. This blog will also consist of all the associated knowledge needed for a better understanding of AWS Transcribe.

Table of content

• What is AWS Transcribe?
• Why AWS Transcribe?
• Speech-to-Text: What and Why
• Accessing AWS Transcribe
• AWS Transcribe Pricing
• AWS Transcribe vs Google Speech-to-Text
• Conclusion

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What is AWS Transcribe?

In the first section of our blog, we are going to discuss the topic in detail. Amazon Transcribe is a new release in the field of text-to-speech which happens to be highly scalable.

• It is a type of on-demand service launched by Amazon based on AWS which is used to convert speech to text.
• It analyses the different types of audio provided by the S3 storage. The transcription generated by this system is very accurate, furthermore, it also provides time stamps.
• One of the best features of this system is that Amazon transcribe is capable of generating text from real-time audio as well, with the same amount of accuracy and resources.
• It supports multiple languages for the conversion but, for real-time only 5 languages are supported yet.
• The best part while using transcribe is that it is capable of identifying different speakers at the same time, you just have to submit the number of speakers that you want AWS to transcribe to recognize.
• It is based on the concept of AI ML, which means it gets better as you use it.

Why AWS Transcribe?

In this part of the blog, we’ll go over the reasons why you should give Amazon web Service Transcribe more thought in this rapid technological advancement. Read the points provided below to learn how this new release has surpassed the previous best in the market. There are several situations where we can use Amazon Transcribe more effectively compared to its competitors.

• AWS’s Transcribe is number one since its stable release in the market with the highest rating of 7.7 out of 10.
• It is used to convert audio from various sources, and various speakers into text accurately and efficiently.
• Because of the features of Amazon Transcribe, it is easy to generate subtitles and captions based on the speech played.
• Amazon Web Service Transcribe has an option for custom vocabulary for users.
• The speech-to-text conversion model used by Amazon Transcribe is full-time managed by Amazon plus the model is continuously trained.
• Transcribe works over AI & ML which makes it up for getting better after every use.

Speech-to-Text: What and Why

Speech-to-text software was initially designed for desktop environments, but the rise of mobile devices has made the developers of developing the same applications for mobile devices.

• The use of speech-to-text technology increases workplace inclusiveness and improves productivity for developers.
• It is a type of technology known as “Speech-to-Text” that combines computer science, engineering, and computational linguistics to allow computers to recognize spoken language and convert it into written text.
• To create emails, it provides helpful notes in the form of transcripts from meetings and events and also provides accessibility. Speech-to-text is being used rapidly and effectively by the concerned organisations.
• Accessibility has exponentially improved by integrating voice synthesis technologies into business operations.
• Speech-to-Text systems improve working conditions by minimizing typing time.
• Speech-to-Text is a solution for those who have trouble typing using traditional input techniques.

Accessing AWS Transcribe

This part is the heart of the blog here. We will discuss the ways how you can access it, read the portion thoroughly as this is our final dive into the topic.

There are two ways to access it. The first one is AWS Console and the second is using Python SDK. In the blog, we are discussing the second way of accessing it.

For this tutorial, we are using Python3. Check out the below-mentioned codes. We will be using software like Google Colab, GitHub, and any python IDE.

• Code For Environment Initialization –

• Code to Generate Access Key –

• Code to handle Duplicate Requests –

• Code for Speaker Recognition –

• Code for adding Speaker Label –

• Code for Inputting File –

• Code for Uploading File to S3 –

AWS Transcribe Pricing

In this part of the blog, we are going to discuss the pricing scheme of Amazon Web Service Transcribe.

• While using Amazon Transcribe, the system says you have to pay per use.
• The price is calculated based on the monthly transcribing seconds used by the users.
• After signing up for the services, you get free 60 mins/month for a year. It comes with a monthly transcription time. This is known as the free tier.
• After the Free Tier expires, there is an additional billing cost of $0.0004 for every audio second utilized.
• Transcribe is charged in 15-second minimum blocks with 1-second increments. Thus, the price for 15 seconds of transcription of audio is $0.06. It would cost $4.80 for 200 minutes of audio every month.

AWS Transcribe vs Google Speech-to-Text

Check out the below-prepared table for the differentiating features between AWS Transcribe and Google Speech-to-Text.

Conclusion

Congratulations on finishing the blog, where we discussed Amazon Transcribe, how to access it using Python, and the costs associated with utilizing it. It is a service launched by Amazon based on AWS, which is outshining its most promising rivals in the market and has shown exponential growth after its release. It has shown potential growth over a period of time and it is here to stay in the market.

Utilizing Amazon Transcribe as a service will be beneficial for businesses that process audio files and want a transcription service to perform analysis on the audio. With this last statement about Amazon Web Service Transcribe, we end the blog here, I hope you learned something new.