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Localize content into multiple languages using AWS machine learning services

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Over the last few years, online education platforms have seen an increase in adoption of and an uptick in demand for video-based learnings because it offers an effective medium to engage learners. To expand to international markets and address a culturally and linguistically diverse population, businesses are also looking at diversifying their learning offerings by localizing content into multiple languages. These businesses are looking for reliable and cost-effective ways to solve their localization use cases. Localizing content mainly includes translating original voices into new languages and adding visual aids such as subtitles. Traditionally, this process is cost-prohibitive, manual, and takes a lot of time, including working with localization specialists.


Amazon expands machine learning services ahead of re:Invent

ZDNet

Amazon Web Services on Tuesday announced new capabilities for three of its AI services -- the text-to-speech service Amazon Polly, the real-time translation service Amazon Translate; and the multi-language transcription service Amazon Transcribe. The expanded capabilities follow a series of similar announcements made recently, all in advance of the annual AWS re:Invent conference. Last year's re:Invent conference was used to roll out a slew of new services, with many bringing customers new machine learning capabilities -- including Amazon Translate and Amazon Transcribe. AI and machine learning are quickly moving from a competitive advantage in the cloud to table stakes, so it makes sense for AWS to improve its existing services ahead of this year's conference. Specifically, Amazon is announcing support for 14 new languages, distinct accents and voices across Polly, Translate and Transcribe.


How AWS AI Services Can Help You Improve Your Foreign Language

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AWS provides several Artificial Intelligence (AI) services. With AI services, you could implement some useful AI things: image and video analysis, document analysis, text to speech or speech to text translation, and so on. However, those AWS services can be used not only for enterprise applications but for your self-development applications. Applying these services we are able to implement an application to improve our foreign language skills. Let's map AWS AI services to language skills: It doesn't cover all skills but we could develop some of them this way.


How To Transcribe Streams of Audio Data in Real-Time with Python?

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In my previous blog posts, I went through the AssemblyAI speech-to-text API. I tried its core transcription service and played with some of its cool AI-powered features: the content moderation feature that spots sensitive topics and the topic detection feature that extracts the subjects that are spoken about in each audio segment. You can check it out here. The code is also available on Github.) These experiments are all performed offline and take some time to run in order to generate the output.


Create video subtitles with Amazon Transcribe using this no-code workflow

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Subtitle creation on video content poses challenges no matter how big or small the organization. To address those challenges, Amazon Transcribe has a helpful feature that enables subtitle creation directly within the service. There is no machine learning (ML) or code writing required to get started. This post walks you through setting up a no-code workflow for creating video subtitles using Amazon Transcribe within your Amazon Web Services account. The terms subtitles and closed captions are commonly used interchangeably, and both refer to spoken text displayed on the screen.