Amazon Transcribe is one of Amazon Web Services' (AWS) machine learning offerings. You input audio or video; Transcribe converts it to text, allowing you to identify the languages used and the number of speakers in the process. You can then take this transcription and do multiple things with it, including search, analytics, subtitles, translations, or even feeding it back into Amazon Polly to read your transcription back to you. When you start a Transcribe job, you're asked to pick out the language that's being spoken -- or have Transcribe automatically detect it for you. Also, there was really no rhyme or reason to the words and phrases I picked, other than they were the first that came to mind!

If you operate in a country with multiple official languages or across multiple regions, your audio files can contain different languages. Participants may be speaking entirely different languages or may switch between languages. Consider a customer service call to report a problem in an area with a substantial multi-lingual population. Although the conversation could begin in one language, it's feasible that the customer might change to another language to describe the problem, depending on comfort level or usage preferences with other languages. With a minimum of 3 seconds of audio, Amazon Transcribe can automatically identify and efficiently generate transcripts in the languages spoken in the audio without needing humans to specify the languages.

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.

Imagine a surgeon taking video calls with patients across the globe without the need of a human translator. What if a fledgling startup could easily expand their product across borders and into new geographical markets by offering fluid, accurate, multilingual customer support and sales, all without the need of a live human translator? What happens to your business when you're no longer bound by language? It's common today to have virtual meetings with international teams and customers that speak many different languages. Whether they're internal or external meetings, meaning often gets lost in complex discussions and you may encounter language barriers that prevent you from being as effective as you could be.

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.

It happens when Google Speech-To-Text and Amazon Transcribe, both popular automatic speech recognition (ASR) systems, erroneously give such age-inappropriate subtitles on YouTube videos for children. This is the key finding of a study titled'Beach to bitch: Inadvertent Unsafe Transcription of Kids Content on YouTube' which covered 7,013 videos from 24 YouTube channels. Ten per cent of these videos contained at least one "highly inappropriate taboo word" for children, says US-based Ashique KhudaBukhsh, an assistant professor at Rochester Institute of Technology's software engineering department. KhudaBukhsh, assistant professor Sumeet Kumar of Indian School of Business in Hyderabad and Krithika Ramesh of Manipal University, who conducted the study, have termed the phenomenon "inappropriate content hallucination". "We were mind-boggled because we knew that these channels were watched by millions of children. We understand this is an important problem because it is telling us that the inappropriate content may not be present in the source but it can be introduced by a downstream AI (Artificial Intelligence) application. So on the broader philosophical level, people generally have checks and balances for the source, but now we have to be more vigilant about having checks and balances if an AI application modifies the source. It can inadvertently introduce inappropriate content," KhudaBukhsh, who has a PhD in machine learning and is from Kalyani in West Bengal, told The Sunday Express.

Real-time feedback helps drive learning. This is especially important for designing presentations, learning new languages, and strengthening other essential skills that are critical to succeed in today's workplace. However, many students and lifelong learners lack access to effective face-to-face instruction to hone these skills. In addition, with the rapid adoption of remote learning, educators are seeking more effective ways to engage their students and provide feedback and guidance in online learning environments. Bongo is filling that gap using video-based engagement and personalized feedback.

If you're looking to take your productivity up a notch (or if you're just a really slow typist), the best speech-to-text software is a sure way to do it. The idea is pretty simple: You speak, and the software detects your words and converts them into text format. The applications are nearly endless, from dictating thoughts and jotting down notes to creating long-form documents without having to type a word yourself. Yet despite this, not many businesses and professionals are taking full advantage of what speech-to-text software can give them. The good news is that the best speech-to-text software doesn't have to cost an arm and a leg -- or anything at all, depending on your needs.

If you are using the Amazon Transcribe service for automated speech recognition (ASR) feature in your project (especially for the English language), you had to decide whether to build a custom language model or a general model provided by AWS transcribe service. It could also be the case that you tried both options in your application. As I had some experience in trying both options in my project, here I am going to share my two cents. You used the general model to transcribe your audio or video files. You noticed that Amazon Transcribe is not able to recognize certain not-so-frequent English words or phrases that have been pronounced by speakers in audio files.

Your contact center connects your business to your community, enabling customers to order products, callers to request support, clients to make appointments, and much more. When calls go well, callers retain a positive image of your brand, and are likely to return and recommend you to others. And the converse, of course, is also true. Naturally, you want to do what you can to ensure that your callers have a good experience. Contact Lens for Amazon Connect provides real-time supervisor and agent assist features that could be just what you need, but you may not yet be using Amazon Connect.