Amazon Transcribe is a powerful tool; it performs transcription with incredibly high accuracy, which grows every day. F1’s use-case was extremely challenging; the combination of incredibly high speed and dynamic commentary from multiple contributors, a global vocabulary and niche technical terminology. Working in close collaboration with AWS, we built and trained a scalable subtitling solution with accuracy and performance that matches human Closed Captioners.

We selected Amazon Transcribe to power the captioning of NASCAR’s VOD content on our multi-site website spanning 195 countries and 29 languages. With Amazon Transcribe, we were able to build an automated system that is almost entirely hands off for our team while giving us the ability to control how to customize the speech recognition for our needs. Since implementing Amazon Transcribe, we automatically add captions to 99% of our VOD content and spend 97% less than what we had originally estimated.

 Amazon Transcribe enables Bongo’s Auto Analysis™ to quickly and accurately transcribe learner videos and provide feedback on the video that helps a learner employ a ‘practice, reflect, improve’ loop. This enables learners to increase content comprehension, retention, and learning outcomes, and reduces instructor assessment time since they are viewing a better work product. Teachers can focus on providing insightful feedback without spending time on the metrics the Auto Analysis™ produces automatically.

 

The Echo360 platform fosters active and engaging video-based learning that serves today’s student. We’re excited about Amazon Transcribe because it offers our university partners high-quality transcripts for each video, enabling more powerful search, lower cost captioning of educational video content, and enhanced note-taking, making learning assets more valuable and accessible to students.

In our mission to provide customers with fair and transparent pricing along with excellent service, we analyze millions of minutes of contact center calls each month. We’ve leveraged our own domain-specific data to train custom speech recognition models using Amazon Transcribe. These custom models provide enhanced transcription accuracy and enable us to more efficiently and intelligently identify, understand, and serve our customers’ energy needs.

With AWS Post Call analytics solution, Principal can currently conduct large-scale historical analytics to understand where customer experiences can be improved, generate actionable insights, and prioritize where to act. Now, we are adding generative AI using Amazon Bedrock to help our business users make data-driven decisions with higher speed and accuracy, while reducing costs. We look forward to exploring the post call summarization feature in Amazon Transcribe Call Analytics in order to enable our agents to focus their time and resources engaging with customers, rather than manual after contact work.

Deliveroo also uses ML and artificial intelligence (AI) tools powered by data to provide a better experience in its contact center. Amazon Connect, an omnichannel cloud contact center, integrates with Amazon Transcribe to automatically convert speech to text. That text can then be analyzed using Contact Lens for Amazon Connect to better understand the reasons customers are calling and any snags in the Deliveroo care experience, allowing the company to improve its practices.

In pharmacovigilance, we want to accurately review recorded calls from patients or Health Care Providers, in order to identify any reported potential side effects associated with medicinal products. Amazon Transcribe Medical produces text transcripts from recorded calls that allow us to extract meaningful insights about medicines and any reported side effects. In this way, we can quickly detect, collect, assess, report, and monitor adverse effects to the benefit of patients globally.

Extreme accuracy in clinical documentation is critical to workflows and overall caregiver satisfaction. By leveraging Amazon Transcribe Medical's transcription API, Cerner is in initial development of a digital voice scribe that automatically listens to clinician-patient interactions and unobtrusively captures the dialogue in text form. From there, our solution will intelligently translate the concepts for entry into the codified component in the Cerner EHR system.

Eva Life Science specializes in building healthcare applications. With more and more voice-enabled apps, we needed a reliable medical speech-to-text building block for the long term. Amazon Transcribe Medical provides us state-of-the-art medical speech recognition and speaker identification in the form of consumable APIs. It makes integrating into our builds easy and scalable.

At OmniMind Technologies, our charter is to help ‘sensify’ the world. In healthcare, making facilities smarter and more intuitive is part of our mission to help providers deliver high quality patient care. We are counting on Amazon Transcribe Medical to enable our devices’ ability to capture medical conversations in real-time and also identify speakers, so that we can feed the accurate transcripts into downstream analytics applications for a multitude of business purposes.

Using Amazon Transcribe, Livongo also derives intelligence from thousands of conversations, both online and by phone, between members and Livongo’s network of health coaches. “We can digitize those, then use natural language processing to really understand what’s happening in our coaching sessions: topics people talk about at an aggregate level and also at an individual level. It helps us learn and look for patterns at scale, then take that information and personalize the rest of a member’s care.

SoundLines supports HealthChannels' skilled labor force at the point of care by incorporating meaningful and impact focused technology such as Amazon's medically accurate speech-to-text solution, Amazon Transcribe Medical, into the workflows of our network of Care Team Assistants, Medical Scribes and Navigators. This allows the clinicians we serve to focus on patients instead of spending extra cycles on manual note taking. Amazon Transcribe Medical easily integrates into the HealthChannels platform, feeding its transcripts directly into downstream analytics. For the 3,500 healthcare partners relying on our care team optimization strategies for the past 15 years, we've significantly decreased the time and effort required to get to insightful data.

AWS is able to assist us in focusing on the things that really count: our core mission, our core product, and our core competency.

At Northwestern Mutual, we wanted to reduce the amount of time our financial representatives spent logging compliant case notes for each of their clients. We originally created an app with a voice-to-text feature that used a phone’s native capabilities, but only 12 percent of financial representatives used it because it took longer to correct the transcribed notes than to type it themselves. To best solve the low adoption problem and provide far greater accuracy, we needed to think of a new approach. Amazon Transcribe stood out as the most accurate platform with the fewest transcription issues – for our use case, we estimated the accuracy to be around 95 percent, whereas other services we looked at were in the 70-percent range.

Transcription is step one for anticipating the needs of customers who call us, and we build on top of it. Because AWS services do their job so well out of the box, we have the flexibility to be creative and build things on top of them.

Every day we analyze 225,000 minutes of live talk radio to create thousands of short, topical segments of information for playlists and search. We chose Amazon Transcribe because it is a remarkable speech recognition engine that helps us transcribe live audio content for our downstream content production work streams. Transcribe provides a robust system that can simultaneously convert a hundred audio streams into text for a reasonable cost. With this high-quality output text, we are then able to quickly process live talk radio episodes into consumable segments that provide next-gen listening experiences and drive higher engagement.

When evaluating a speech-to-text service, we focused on finding a service that could create a safe community for our users by automatically redacting banned words. These banned words are typically slang and not recognized by standard speech-to-text services. With Amazon Transcribe and its custom vocabulary feature, banned terminology can be identified and redacted. Looking forward, our team is excited to grow the Voice Pococha community with the support of services like Amazon Transcribe and the Amazon Web Services (AWS) team.

At Isentia, we enable customers to analyze and monitor the media coverage for their brands. We create more than 13K summaries per day from radio and TV content. With Amazon Transcribe, we can transcribe all the audio/video content that we monitor and analyze the text data with Amazon Comprehend. Features like timestamps and punctuation make it very easy for us to search through the data and drill down and present key insights for our customers to review.

Replica imagines a future where a user’s own voice could be the voice of the main character in their game, podcast, advertisement, or film. AWS is the engine behind Replica’s cutting-edge generative voice technology. We’re using AWS all the way from R&D to production, leveraging EC2, EFS, SQS, and CloudWatch for core compute support, AMIs as we scale, and Amazon Transcribe to go from audio to text files. Our tech stack enables game developers to place players at the center of fully immersive experiences and create highly personalized stories; podcasters can supercharge their content; and pioneering filmmakers can spearhead a new wave of interactive movies. With AWS is our primary AI/ML solution, we’re excited to be at the forefront of the next generation of content creation.

Traditional methods of content localization have been a major barrier preventing MagellanTV from entering global markets due to high per-minute charges. Magellan TV worked with Mission Cloud, an AWS Partner to built a fully automated pipeline to translate, transcribe, and dub content with generative AI and AWS services such as Amazon Transcribe and Amazon Translate. Now MagellanTV can vastly reduce the resources needed to share its content on a global scale. In addition to time savings, costs have also been dramatically reduced. “We were talking about somewhere like US$20 a minute to get content dubbed using traditional methods. Now we’re looking at less than US$20 an hour.”

We're transforming the traditional ways of consumer research by introducing video and automating the analysis of this video to result in actionable, dynamic consumer personas. Integrating with AI and machine learning technologies from Amazon, such as Amazon Transcribe, Amazon comprehend, and Amazon Rekognition, we're able to take these videos, analyze them, and create profiles of each individual.

Amazon Comprehend and Amazon Transcribe allow VidMob to build high-quality machine learning text analysis into our Agile Creative Suite, enabling us to help brand clients understand content performance in ways never before possible. We are able to transcribe text from video content, and quickly analyze it using Comprehend, allowing us to surface actionable insights to both our creator community and our clients, giving them a strategic edge in the market.

GE Appliances processes millions of minutes of customer calls a month. Using Amazon Connect, Amazon Lex, and Amazon Polly, we can automate simple tasks such as looking up product information, taking down customer details, and answering common questions before an agent answers. This in turn helps us give back time, the most precious commodity, to our consumers. We added Amazon Transcribe to create call transcripts for automated analysis to continuously improve the process.

AWS provides world-class transcription (Amazon Transcribe) and translation (Amazon Translate) as the foundation for our large language models to help users around the world better connect with their friends, family, and surroundings. Coupled with Amazon Cognito and AWS Lambda functions, we can provide these services to our users in a secure, scalable, reliable and cost-effective manner.

With SuccessKPI, we were able to add AWS Contact Center Intelligence into our Genesys Cloud environment in a matter of hours and deliver a 360-degree view of the citizen experience. This program allowed us to deliver increased capacity, automated quality review, and agent compliance and performance improvements for government agencies..

We’ve taken advantage of the advances in AI, machine learning (ML), and cloud computing to reimagine qualitative market research and developed a scalable solution that is equipped to perform speech-to-text conversion and natural language processing (NLP) on the audio recordings of interviewed subjects. Using Amazon Transcribe, Amazon Comprehend Medical, and custom NLP for text summarization and graph visualization, we have created a scalable, automated solution that helps us provide insights in a faster, better, and more efficient way.

AI-powered Carbyne Live Audio Translation is directly aimed at helping improve emergency response for the 68 million Americans who speak a language other than English at home, in addition to the up to 79 million foreign visitors to the country annually. By leveraging Amazon Transcribe’s new multilingual foundation model powered ASR, Carbyne will be even better equipped to democratize life-saving emergency services, because Every. Person. Counts.

On AWS, Epiq not only built a cost-effective solution that enabled it to automate, accelerate, and increase the accuracy of legal transcription, but it also revolutionized the way transcription is completed in the industry. In a few weeks, Epiq delivered an AWS-powered transcription solution that is 5% more accurate than other third-party transcription engines and reduces costs by a factor of 15x.

Facing the challenge of persistent transcription errors in our cloud service, Remote Legal turned to AWS for a solution. The migration to Amazon Transcribe was completed in a week, virtually eliminating transcription errors. The results have been remarkable - achieving a 98% success rate. The power and reliability of AWS has enabled Remote Legal to offer a frictionless experience to their customers.

The future of enterprise software will be driven by the combination of cloud services and workstream collaboration tools. Strategically partnering with AWS allows both companies to scale to meet demand and deliver enterprise-grade offerings to our customers.

Amazon Transcribe is a highly accurate, easy to use speech to text service that contains many features for customization and the call center use case. With Amazon Transcribe, we have been able to build a sentiment analysis solution that has expanded our customer sentiment visibility from 12% to 100%.