AWS Machine Learning Blog
Category: Amazon Transcribe
Unearth insights from audio transcripts generated by Amazon Transcribe using Amazon Bedrock
In this post, we examine how to create business value through speech analytics with some examples focused on the following: 1) automatically summarizing, categorizing, and analyzing marketing content such as podcasts, recorded interviews, or videos, and creating new marketing materials based on those assets, 2) automatically extracting key points, summaries, and sentiment from a recorded meeting (such as an earnings call), and 3) transcribing and analyzing contact center calls to improve customer experience.
Unlock organizational wisdom using voice-driven knowledge capture with Amazon Transcribe and Amazon Bedrock
This post introduces an innovative voice-based application workflow that harnesses the power of Amazon Bedrock, Amazon Transcribe, and React to systematically capture and document institutional knowledge through voice recordings from experienced staff members. Our solution uses Amazon Transcribe for real-time speech-to-text conversion, enabling accurate and immediate documentation of spoken knowledge. We then use generative AI, powered by Amazon Bedrock, to analyze and summarize the transcribed content, extracting key insights and generating comprehensive documentation.
Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations
In this post, we discuss how you can use AWS HealthScribe with Amazon Q Business to create a chatbot to quickly gain insights into patient clinician conversations.
Summarize call transcriptions securely with Amazon Transcribe and Amazon Bedrock Guardrails
In this post, we show you how to use Amazon Transcribe to get near real-time transcriptions of calls sent to Amazon Bedrock for summarization and sensitive data redaction. We’ll walk through an architecture that uses AWS Step Functions to orchestrate the process, providing seamless integration and efficient processing
How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines
In this post, we share how DPG Media is introducing AI-powered processes using Amazon Bedrock into its video publication pipelines. This solution is helping accelerate audio metadata extraction, create a more engaging user experience, and save time.
Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS
In this post, we demonstrate how Intact’s Call Quality solution used Amazon Transcribe and other AWS services to improve critical KPIs with AI-powered contact center call auditing and analytics.
Build a serverless voice-based contextual chatbot for people with disabilities using Amazon Bedrock
In this post, we presented how to create a fully serverless voice-based contextual chatbot using Amazon Bedrock with Anthropic Claude.
Generative AI-powered technology operations
In this post we describe how AWS generative AI solutions (including Amazon Bedrock, Amazon Q Developer, and Amazon Q Business) can further enhance TechOps productivity, reduce time to resolve issues, enhance customer experience, standardize operating procedures, and augment knowledge bases.
Elevate healthcare interaction and documentation with Amazon Bedrock and Amazon Transcribe using Live Meeting Assistant
Today, physicians spend about 49% of their workday documenting clinical visits, which impacts physician productivity and patient care. Did you know that for every eight hours that office-based physicians have scheduled with patients, they spend more than five hours in the EHR? As a consequence, healthcare practitioners exhibit a pronounced inclination towards conversational intelligence solutions, […]
Catalog, query, and search audio programs with Amazon Transcribe and Amazon Bedrock Knowledge Bases
Information retrieval systems have powered the information age through their ability to crawl and sift through massive amounts of data and quickly return accurate and relevant results. These systems, such as search engines and databases, typically work by indexing on keywords and fields contained in data files. However, much of our data in the digital […]