Amazon Chime SDK Call Analytics: Real-Time Insights into Audio Conversations

 

Introducing Amazon Chime SDK Call Analytics

The Amazon Chime SDK is a powerful tool that our team at Inmost has been utilizing for years. We have developed a range of solutions based on this technology, including custom communication and collaboration tools for healthcare, education, and other industries. As experts in Chime SDK development, we closely monitor updates and enhancements to the platform.

Earlier, we discussed the benefits of Amazon Chime SDK and how it can be leveraged by businesses to build efficient tools for communication and remote collaboration. Now, the capabilities of Chime SDK have been further enhanced with the introduction of Amazon Chime SDK call analytics. This new feature set makes recording and generating insights on real-time audio calls more accessible and cost-effective through transcription, voice tone analysis, and speaker search. In addition, some improvements were made to the Amazon Chime SDK section of the AWS Management Console. This allows developers to easily integrate machine learning (ML)-based services, such as call analytics capabilities and Amazon Transcribe, into their audio applications with just a few simple steps.

 

Voice analytics pipeline in AWS Chime SDK

At the core of AWS Chime SDK's voice analytics capabilities is a deep learning model trained to recognize different emotions and sentiments expressed in human speech. This model is based on a hybrid architecture combining acoustic and text-based features to extract meaningful insights from voice data.

The voice analytics pipeline begins with automatic speech recognition (ASR) to transcribe spoken words into text. This text is then analyzed using natural language processing (NLP) techniques to extract relevant features such as sentiment, tone, and intent.

The ASR and NLP pipelines are critical components of the voice analytics system, but they can be computationally expensive to run in real time. To address this challenge, AWS Chime SDK leverages a hybrid model that combines acoustic and text-based features to extract insights from voice data in real time.

In this model, the front-end processing of the voice signal is held fixed, and the ASR encoder and decoder parameters are trained using a transcript with a prepended sentiment label. The loss function scores the model on how well it maps input features to the sentiment label and the transcript. The encoder thus learns both tonal information and linguistic information.

Once the ASR training is complete, the classifier branch is constructed using the pre-trained front end and the trained ASR encoder. The encoder output is connected to a lightweight classifier, and the parameters of the front end and the ASR encoder are both frozen. Using sentiment-labelled speech inputs, the classifier is trained to output the probabilities of positive, neutral, and negative sentiments. It is also trained to detect speech presence.

The model is then deployed as a voice analytics capability in Amazon Chime SDK call analytics. In its production configuration, the model is run on five-second voice segments every 2.5 seconds to provide real-time probability estimates for speech presence and sentiment. The model is configured to use the short-term sentiment probabilities to compute sentiment estimates over the past 30 seconds of active speech and over the entire duration of the speech signal.

 

Integrating AI services into telephony applications

The AWS team has introduced an easier-to-use graphical configuration in the Amazon Chime SDK section of the console to simplify the process of adding capabilities to existing telephony applications. This makes it possible for developers to add voice analytics, Amazon Transcribe, or Amazon Transcribe Call Analytics without requiring expertise in telephony, cloud infrastructure, or AI.

Developers can now select the AWS AI service they want to use for analyzing real-time audio data directly from the console. There is no need to write any integration code as AWS manages the integration between the AI services and voice-based or telephony applications. The console allows developers to define where they want to send the analytics data, either to an Amazon Kinesis stream or an Amazon Simple Storage Service (Amazon S3) bucket.

Additionally, voice analytics can send real-time notifications to a function deployed on AWS Lambda, an SQS queue or Amazon Simple Notification Service (Amazon SNS) topic. This integration with AI services through the AWS Management Console helps developers to streamline their development process and focus on improving the customer experience.

 

Visualizing insights and generating real-time alerts

AWS Chime SDK's call analytics capabilities not only provide real-time insights and sentiment analysis but also enable developers to visualize these insights more intuitively. Call analytics delivers analyses to a data lake of your choice, which can then be used to build custom dashboards using tools like Amazon QuickSight or Tableau. These dashboards can be embedded into applications, wikis, and portals, allowing businesses to monitor and analyze customer interactions in real-time.

To further streamline the process, call analytics provides prebuilt dashboards as AWS CloudFormation templates that can be easily deployed into your own AWS account. This simplifies the setup process and allows businesses to get started with monitoring and analyzing their customer interactions quickly.

In addition to visualizing insights, call analytics also can generate real-time alerts. By posting events to Amazon EventBridge, businesses can route these events to any destination of their choice within their AWS account or supported third-party applications. This allows businesses to stay on top of significant customer interactions and respond on time.

 

Benefits across various industries

In regulated industries such as finance and healthcare, recording and analyzing conversations is often a requirement for compliance purposes. With voice tone analysis, trading room supervisors in the finance industry can easily detect and classify cheerful, neutral, or negative tones in trading conversations, allowing them to meet regulatory requirements and deliver insights to traders to improve productivity. Similarly, in healthcare, voice analytics can help providers monitor patient interactions to ensure compliance with privacy and quality standards.

But it's not just regulated industries that can benefit from real-time insights into audio conversations. Businesses in the public sector, telecom, insurance, and can also leverage these capabilities to improve customer service, optimize sales conversations, and enhance employee training.

For example, speaker search can help businesses expedite caller lookup and enrich call records and transcripts with identity attribution, improving customer service and support. Voice tone analysis can also help sales teams better understand customer sentiment during calls and adjust their approach accordingly to increase conversion rates. And in the BPO industry, voice analytics can be used to monitor and improve agent performance during customer interactions.

By leveraging real-time insights into audio conversations, businesses can make more informed decisions, improve customer experiences, and enhance productivity and efficiency across their operations.

 

Enhancing customer experience with AWS Chime SDK's call analytics

Our team believes these new features will be valuable additions to Chime and make it more efficient for businesses to communicate and collaborate remotely, reducing the time and resources needed to generate insights from real-time audio data.

We are already negotiating the possibility of integrating new voice analytic features into our existing Amazon Chime-based solution with one of our trusted partners, a marketing agency.

Our proposed voice analytics features will provide an in-depth analysis of call quality, customer engagement and satisfaction, and call duration. This data will be leveraged to generate valuable insights and recommendations to optimize the agency's voice call experiences.

We are thrilled to have contributed to the continued evolution of Amazon Chime SDK. We look forward to continuing our work with AWS to enhance Chime SDK further and provide more value to our clients and users.

 

 

Simplifying blockchain networks with managed services: A look at Amazon Managed Blockchain

 

Challenges of building and maintaining blockchain networks.

Blockchain technology has considerably changed how we think about secure and transparent transactions, enabling the creation of applications where multiple parties can carry out transactions without needing a trusted central authority.

But today, creating a scalable blockchain network using existing technologies is still complex and challenging to manage. To build a blockchain network, each participant in the network must manually provide hardware, install software, create and manage certificates for access control, and configure network components. Once a blockchain network is up and running, the infrastructure must be constantly monitored and adapted to changes, such as an increase in transaction requests and new participants joining or leaving the network.

To solve this problem, cloud service providers such as Amazon Web Services (AWS) have developed managed blockchain services that allow companies to quickly build and manage their blockchain networks without worrying about the underlying infrastructure.

 

We are simplifying the creation and management of blockchain networks.

Amazon Managed Blockchain is a fully managed service that simplifies creating and managing scalable blockchain networks. It allows users to join public networks or create and manage private networks for enterprises, using popular open-source platforms such as Hyperledger Fabric and Ethereum

With Amazon Managed Blockchain, companies can quickly and easily create a private Hyperledger Fabric blockchain network and add partner organizations using their AWS account ID. In addition, developers can utilize Ethereum Mainnet nodes supported by Amazon Managed Blockchain to create decentralized applications and services on top of the Ethereum blockchain. Using an Ethereum node on Managed Blockchain, users can build an NFT marketplace or analyze Ethereum blockchain data with their dedicated node. Furthermore, Managed Blockchain maintains the Ethereum Full node by automatically upgrading the node client software as updates are released.

In addition, Amazon Managed Blockchain Hyperledger Fabric is supported in GovCloud, enabling government agencies and contractors to deploy in environments specifically designed to host sensitive data and address the most stringent U.S. government security and compliance requirements.

 

Benefits of using Amazon Managed Blockchain.

Using a blockchain service, like Amazon Managed Blockchain, offers several benefits compared to self-hosted blockchain solutions. One of the main benefits is reduced costs, as users no longer need to worry about purchasing hardware, installing and maintaining software, and configuring network components. With a managed service, all of these tasks are taken care of, allowing users to focus on developing their blockchain applications and services.

Another advantage of using a managed blockchain service is improved scalability. Scaling a blockchain network can be challenging, requiring significant technical expertise and resources. However, with a managed service, scaling is more accessible as the cloud service provider manages the underlying infrastructure. This means that users can easily add new participants to the network, handle increasing transaction volumes, and adapt to changing business needs.

Advanced security: managed blockchain services often have built-in security features that can help protect your network against attacks and unauthorized access. For example, Amazon Managed Blockchain offers built-in identity and access management (IAM) tools that allow you to manage access to your network, as well as built-in encryption and key management features to help protect your data.

Managed blockchain service can be precious if you're working on a tight deadline or need to get your product to market quickly. By using it, you can often get your network up and running faster than if you were building and maintaining it yourself, providing faster time-to-market.

Amazon Managed Blockchain provides the flexibility to use popular open-source blockchain platforms such as Hyperledger Fabric and Ethereum to create and manage private or public blockchain networks. Hyperledger Fabric is an enterprise-grade, modular blockchain framework that provides a plug-and-play architecture, enabling developers to customize their blockchain applications. Ethereum, on the other hand, is a decentralized blockchain platform that provides a flexible and programmable infrastructure for developing decentralized applications.

Fabric's architecture is designed to support permissioned networks with more control over the participants and their access to data. In contrast, Ethereum is designed for permissionless networks where anyone can participate and interact with the network.

With Amazon Managed Blockchain, users can choose the blockchain platform that best suits their needs and can take advantage of the fully managed service provided by AWS.

 

Managed blockchain use cases.

Managed blockchain services and blockchain frameworks can be used to create a wide range of blockchain applications and services. For example, companies can build supply chain management systems where each participant can track the movement of goods and verify the product's authenticity using Hyperledger Fabric. Alternatively, they can build decentralized applications and services on top of the Ethereum blockchain, such as NFT marketplaces or data analysis tools. Government agencies and contractors can also utilize Amazon Managed Blockchain Hyperledger Fabric in GovCloud to deploy blockchain networks in environments designed to host sensitive data and comply with U.S. government security and compliance requirements.

These are just a few examples of applications that can be built using managed blockchain services and blockchain frameworks. The flexibility and customization options provided by these services make it possible to create a wide variety of blockchain-based applications tailored to specific business needs.

 

Leveraging Hyperledger Fabric and Ethereum for your blockchain solution.

Inmost, the team has experience working with Hyperledger Fabric and Ethereum within the AWS Managed Blockchain platform. We have successfully implemented Hyperledger Fabric in healthcare, improving trust in sharing documents for telehealth services and providing transparency in apartment rental services. Additionally, we have built an NFT-based solution that assigns ownership to game artefacts.

We understand that improving business processes can be a daunting task, but our team is here to help. Our expertise in blockchain technology can help you leverage the benefits of AWS Managed Blockchain to create innovative solutions that streamline your business processes and increase transparency and trust.

So, if you're looking to improve your business processes and take advantage of the benefits of blockchain technology, don't hesitate to contact us. Our team of experts is ready to work with you to deliver customized solutions that meet your unique business needs. Let's work together to transform your business for the better.

 

Enhancing Collaboration with Amazon Chime: A Guide to CPaaS Solutions

Enhancing Collaboration and Engagement with Cloud-Based Communication Tools

 

Remote work and education have become increasingly popular in recent years, with more organizations adopting flexible work arrangements and digital learning platforms. While these trends offer many benefits, they also present unique challenges for communication and collaboration. For example, remote teams and learners may struggle to stay connected and engaged, decreasing productivity and performance.

To address these challenges, many organizations are turning to CPaaS (Communication Platform as a Service) solutions, which provide cloud-based platforms for integrating communication features into applications. These solutions offer a range of communication channels, such as voice, video, messaging, and chat, and integration with other services, such as CRM and marketing automation. 

CPaaS enables organizations to easily integrate communication features into their applications, enhancing remote team and learner engagement and collaboration.

One popular CPaaS solution is Amazon Chime, which offers a range of features designed to help businesses and educational institutions communicate and collaborate more effectively. In this article, we'll explore the benefits of Amazon Chime and how it can help organizations succeed in the remote work and digital learning era. We'll also take a closer look at CPaaS solutions and how they can help organizations overcome the challenges of remote work and education. Whether you're a business or an educational institution, this article will provide valuable insights into how CPaaS solutions like Amazon Chime can help you improve communication and collaboration among remote teams and learners.

 

Amazon Chime features and benefits

Amazon Chime is a CPaaS solution streamlines communication and collaboration for remote teams and learners. It is cloud-based, which means that users can access it from anywhere as long as they have an internet connection. Amazon Chime offers a wide range of features:

Video Conferencing: Amazon Chime's video conferencing feature allows teams to connect face-to-face, even when they're not in the same room. Featuring high-quality audio and video, Amazon Chime enables virtual meetings that closely replicate in-person interactions and can range from small in-house meetings to large conferences and virtual events, hosting up to 250 participants. With the recent update to Amazon Chime SDK, presenters can now deliver real-time media to up to 10,000 participants. Participants can be brought "on stage" with their existing WebRTC connection, allowing them to contribute to the live conversation without missing a moment of content. 

Each WebRTC media session supports 250 connections, and can be replicated up to 40 times for an additional 10,000 participants. Additionally, participants connected to a replica session can be granted access to join the primary session, and because everyone is using WebRTC, there is no transcoding delay between presenters and participants. Media replication is ideal for webinars and other use cases where privacy is desired, as participants connected to a replica session receive only the content of the presenters connected to the primary session and do not have visibility of other participants.

Screen Sharing: Amazon Chime's screen-sharing feature enables team members to share their screens with others during virtual meetings. This is especially useful when discussing complex ideas or when multiple people need to work on the same project simultaneously. Screen sharing helps teams stay on the same page and ensures everyone works towards the same goal.

Chat: Amazon Chime's chat feature allows teams to send instant messages to each other, making it easy to communicate quickly and efficiently. With the ability to create group chats, teams can collaborate on projects and share ideas in real time. This feature helps reduce email overload and ensures essential information is shared with the right people at the right time.

File Sharing: Amazon Chime's file-sharing feature enables teams to share files during virtual meetings. This feature makes it easy to collaborate on projects and share essential documents without email attachments. By eliminating the email need, teams can save time and focus on what's important.

All mentioned functionality allows teams to connect face-to-face, share ideas, and work on projects together, regardless of their physical location. The benefits of Amazon Chime's features include improved collaboration, increased productivity, and better communication. By using Amazon Chime, organizations can overcome the challenges of remote work and digital learning and achieve better outcomes.

 

Ease of use

Amazon Chime is known for its user-friendly API and ease of integration, making it a popular choice for organizations looking for a reliable communication and collaboration platform. With Amazon Chime, developers can effortlessly create custom applications that allow users to join meetings and collaborate with team members from anywhere, at any time, using any device. The API is well-documented and easy to work with, enabling developers to integrate communication features without extensive technical expertise quickly. Overall, Amazon Chime's ease of use helps to minimize development time and onboarding efforts, allowing teams to get up and running quickly and efficiently. 

 

Data security

Data security is a top priority for businesses, especially when it comes to communication and collaboration tools. Amazon Chime recognizes this and has taken several measures to ensure the security of its users' data. Here are some of the security features of Amazon Chime:

End-to-end encryption: Amazon Chime uses end-to-end encryption to ensure all user communication is secure and private. This means that only the sender and the intended recipient can read the messages, and no one else can intercept or access the data.

AWS infrastructure security: Amazon Chime is built on the secure and reliable infrastructure of Amazon Web Services (AWS). AWS has extensive security features, including access control, data encryption, and monitoring, to protect data stored on its servers.

Compliance with regulatory requirements: Amazon Chime is compliant with various regulatory requirements, such as HIPAA and GDPR, to ensure that users' data is protected and stored securely. Businesses can use Amazon Chime to communicate and collaborate with their colleagues and clients without worrying about data security.

Amazon Chime's security features help to ensure that users' data is protected, giving businesses peace of mind when using the platform for communication and collaboration.

 

Integration with other AWS services

Amazon Chime is designed to work seamlessly with other Amazon Web Services providing users with a more streamlined experience and increased productivity.

For example, the integration of Amazon Chime with Amazon WorkSpaces allows users to join meetings directly from their WorkSpaces desktop. This means they don't have to switch between applications to attend a meeting, improving performance and saving time.

When Amazon Chime is integrated with Amazon Connect, a cloud-based contact centre service that offers voice and chat communication channels for customer service, it allows agents to join meetings directly from their Amazon Connect console quickly. This integration not only enables more efficient collaboration among agents, but also offers a smoother and more seamless experience for customers. By combining the communication capabilities of Amazon Chime with the customer service features of Amazon Connect, businesses can provide a more comprehensive and effective solution for their customer support needs.

Amazon Chime can integrate with other AWS services to create customized solutions that meet specific business needs. Businesses can leverage the flexibility and scalability of AWS to build powerful tools that suit their unique requirements. The possibilities for integration with AWS are virtually endless, making Amazon Chime a highly versatile platform that can be tailored to fit the needs of any organization.

 

Inmost team experience and expertise

The Inmost team has successfully implemented numerous customized solutions using Amazon Chime across various sectors, including healthcare, education, and social networks. We are dedicated to working closely with our clients to understand their unique needs and challenges, and developing tailored solutions that optimize their business processes, enhance communication, and promote effective collaboration.

We understand that adapting to the remote work and digital learning era can be challenging, and we are here to guide you every step of the way. By partnering with Inmost, you can leverage our expertise and experience to gain a competitive edge and maximize the benefits of Amazon Chime for your organization. Contact us today to learn more about how we can help your organization thrive in this rapidly evolving digital landscape: https://inmost.pro/contact-us/.

 

Unlocking the potential of NLP with AWS services

The increased interest in NLP

Although some users do not share the massive enthusiasm for the ChatGPT, calling it a creativity killer, the ability to accelerate and optimize many processes has made numerous entrepreneurs and businesses increasingly interested in NLP tools involving Artificial Intelligence and Machine Learning. 

 

So, what is NLP? 

NLP stands for Natural Language Processing, a field of study within computer science and artificial intelligence (AI) that focuses on the interaction between computers and human language. NLP involves the development of algorithms and techniques that allow computers to analyze, understand, and generate human language in a way that is very similar to the way humans communicate with each other.

NLP uses various techniques, such as machine learning, deep learning, and neural networks, to help computers understand the nuances of human language. NLP algorithms can be trained on large data sets of human language to learn patterns and structures such as grammar, syntax, and meanings.

For example, ChatGPT is an NLP tool designed to generate human-like responses to input text. When a user enters text, the model generates a response based on the patterns it has learned from the training data. 

Actually, NLP deals with a wide range of tasks, including language translation, speech recognition, sentiment analysis, text classification and information extraction. These tasks are usually performed on unstructured data, such as text documents, audio recordings, and social media messages.

 

How can it benefit businesses?

  • Improving customer service: NLP can be used to automate customer service tasks, such as answering customer requests or distributing queries to the appropriate departments. This can help businesses improve customer satisfaction and reduce the workload of support staff. NLP-powered chatbots and virtual assistants can be used to provide immediate responses to customer queries and provide personalized recommendations. They can also help reduce waiting time and provide 24/7 support.
  • Increasing operational efficiency: NLP-based text analytics automatically extracts information from large amounts of unstructured data, such as customer reviews, social media posts and customer service calls. This can help companies identify trends, track brand sentiment, and gain valuable insights into customer needs and preferences. NLP can automate various business processes, such as content moderation, data extraction and categorization, reducing manual work and streamlining operations.
  • Improving marketing: enables businesses to understand their customers better and deliver more personalized, targeted messaging. Keyword extraction helps identify keywords and topics relevant to an enterprise's target audience, which helps create content and marketing messages. Methods such as sentiment analysis can be used to understand customer feedback and reviews, helping companies learn how their customers perceive their brand and products. This can help justify marketing messages and improve customer interactions.
  • Improving compliance: NLP can automatically detect and flag inappropriate or offensive content in text data, which can help businesses comply with regulations and avoid legal risks. It can automatically monitor regulatory compliance by analyzing documents for relevant keywords, phrases, and patterns, which can be extremely useful for contract management, Anti-Money Laundering (AML), fraud detection, and data privacy compliance.

 

How difficult and expensive is the implementation of NLP?

The complexity and cost of NLP implementation into business processes can vary depending on several factors, including the size of the company and the specific NLP use cases. In general, it can be challenging, time-consuming, and expensive, especially if you want to develop everything from scratch. NLP requires a large amount of data to train and test models and significant computing resources.

But NLP tools can be much more accessible and cost-effective due to cloud services provided by companies such as Amazon Web Services (AWS). These services deliver easy-to-use APIs and pre-built models that can be integrated with other software applications.

 

What are NLP services offered by AWS?

One of the most famous NLP solutions from AWS is probably Alexa. This virtual assistant can understand natural language commands and perform various tasks like playing music, controlling smart home devices, providing weather updates, and answering questions. Alexa uses advanced Natural Language Processing (NLP) techniques to interpret and understand user input.

Alexa was created on top of the Amazon Lex service - a fully managed service providing a platform to build, test, and deploy chatbots and other conversational interfaces that can understand natural language input and respond with appropriate actions. Developers can create custom skills for Alexa using the Lex console, which allows them to define intents and slots, build dialogue flows, and integrate with external services.

Amazon Polly is used to converting generated responses into speech. This text-to-speech service can generate lifelike speech in multiple languages and voices, using deep learning technologies and advanced prosody models, resulting in high-quality, natural-sounding speech output.

A neural machine translation technology is used by Amazon Translate Service to provide high-quality translations. It supports 75 different languages. 

For working with large volumes of data and documents:

  • Amazon Comprehend - NLP service that can extract insights and relationships from text data. It can perform tasks like sentiment analysis, entity recognition, language detection, and keyphrase extraction.
  • Amazon Textract: a service that can extract text and data from scanned documents, forms, and tables.
  • Amazon Kendra: An enterprise search service that uses machine learning to provide natural language search capabilities across multiple data sources, like documents, FAQs, and wikis.

 

These AWS NLP services can be used individually or in combination to build applications that can analyze, understand, and generate natural language.

By integrating these services with other AWS offerings like, for example, a unified communications service - Amazon Chime, companies can create robust and cost-efficient solutions that improve customer engagement and satisfaction and provide assertive communication and collaboration tools for businesses of all sizes, from virtual meetings to contact centres to virtual assistants.

Inmost team has expertise in building solutions that combine AWS services with NLP capabilities, and we can help you create high-performance and cost-efficient solutions that drive business success. 

Don't hesitate to contact: https://inmost.pro/contact-us/

 

Amazon Transcribe Medical

Digitization of the healthcare sector

In recent years, the healthcare sector has begun to actively embrace modern digital solutions - from telemedicine applications, connecting residents of the most remote, “hard-to-reach” regions to world-class medical services, to the use of sensors and devices that help remotely monitor and record patient physical data such as: heartbeat, blood pressure, movement and even behavioral patterns. The unique challenges of Covid-19 have played a decisive role in accelerating the digitization of healthcare, when it became clear that many processes in the healthcare sector require a fundamental transformation.

Currently, medicine has a variety of digital tools to improve communication, administrative and operational processes, data storage and transition.

One such tool that facilitates the work of medical professionals is Transcribe Medical Service from Amazon.

 

What is Amazon Transcribe Medical?

In the past, writing paper reports took doctors a lot of time. And after the beginning of digital transition there is a standard requirement for healthcare providers to enter medical records into Electronic Health Record (EHR) systems on a daily basis. According to a study held by the University of Wisconsin and the American Medical Association in 2017, primary care physicians in the United States spent up to 6 hours a day entering this data.

In 2019, Amazon launched a service built on top of the Amazon Transcribe. It was designed specially for healthcare professionals to transcribe medical-related speech, such as physician-dictated notes, drug safety monitoring, telemedicine appointments and consultations, or conversations of doctors with patients. 

The Amazon Transcribe Medical service uses machine learning and natural language processing (NLP) to accurately convert audio speech or conversation to a text. It is trained to understand complex medical language and special terms and measurements used by doctors. Developers can use Amazon Transcribe Medical for medical voice applications, by integrating with the service’s easy-to-use APIs. Pharmaceutical companies and healthcare providers can use Amazon Transcribe Medical to create services that enable fast and accurate documentation. 

The service can transcribe speech as either an audio file or a real-time stream, the input audio can be in FLAC, MP3, MP4, Ogg, WebM, AMR, or WAV file format. Streaming transcription is available in US English, it can produce transcriptions of accented speech, spoken by non-native speakers.

This service provides transcription expertise for primary care and specialty areas such as cardiology, neurology, obstetrics-gynecology, pediatrics, oncology, radiology and urology. Transcription accuracy can be improved by using medical custom vocabularies.

 

Transcribe Medical use cases

Medical dictation: medical specialists can record their notes by speaking into the microphone of a mobile device during or after interacting with a patient, being able to reduce the administrative workload and focus on providing quality patient care.

Drug safety monitoring: transcribing of phone calls regarding drug appointment and side effects enables more safe service provisioning by pharmaceutical companies and clinics. 

Transcribing of conversations: recording conversations between a doctor and a patient in real time without disrupting the interaction, allows healthcare providers to accurately capture details such as mentioned symptoms, medicine dosage and frequency, side effects. This information can be processed through subsequent text analytics and then entered into Electronic Health Record (EHR) systems.

In case of online video or phone consultations Channel Identification feature can be used. This is a powerful tool allowing to independently transcribe the patient and clinician audio channels and provide real-time conversational subtitles.

 

Benefits of Amazon Transcribe Service

Amazon Transcribe Medical benefits a wide range of healthcare specialists: nurses, physicians, researchers, insurers, and pharmaceutical companies - as well as their patients. The following features make it highly attractive to clinicians and healthcare professionals:

HIPAA (Health Insurance Portability and Accountability Act) eligible: providing support for the automatic identification of protected health information (PHI) in medical transcriptions Amazon Transcribe Medical reduces the cost, time, and effort expended on identifying PHI content through manual processes. PHI entities are labeled clearly with each output transcript, making it convenient to build additional downstream processing for a variety of purposes, such as redaction prior to text analytics.

Highly accurate transcription: the narrow specialization of the service, exclusively aimed  at the needs of the healthcare sector, ensures that even the most complex medical terms, such as the technical names of diseases and medicines, are recorded correctly. 

Improving the patient and practitioner experience: so that the doctor does not have to waste time taking notes and writing reports, but can focus on the patient, accurately transcribing all the details of the consultation or conversation without disrupting the interaction.

Easy to use: no prior knowledge or experience with machine learning is required. Developers can focus on building their medical speech applications by simply integrating with the service's APIs. Transcribe Medical handles the development of state-of-the-art speech recognition models.

Thus, Amazon keeps investing into the medical sector, empowering healthcare and life sciences, and enhancing the number of digital services to deliver patient-centered care, accelerate the pace of innovation and unlock the potential of data, while maintaining the security and privacy of health information.

 

Our experience

With extensive experience in building healthcare applications based on Amazon services and developing long-term partnership with global leaders in telemedicine technologies & services, we, Inmost Company, took the opportunity to ease the burden of reporting and documentation for our clients by integrating Transcribe Medical into the application for remote medical consultations. This has significantly optimized medical staff workload, streamlined processes, and increased positive feedback from patients.

Based on these experiences, we consider Amazon Transcribe Medical Service to be a really important and useful tool for transforming medical services. 

And, of course, we are ready to support healthcare organizations on their digital transformation path by providing consulting services, renovating and improving existing platforms or developing efficient and reliable solutions from scratch.

 

Transcribe

Transcribe Service was launched by Amazon in 2017 enabling developers to implement a speech-to-text feature to their applications.

Analyzing and data extraction from audio files is almost impossible for computers. To use such data in an application, speech must first be converted to text. Services performing speech recognition technologies have certainly existed before, but they were generally expensive and poorly adapted to various scenarios, such as low-quality phone audio in some contact centers.

Powered by deep learning technologies, Amazon Transcribe is a fully managed and continuously trained automatic speech recognition service that automatically generates time-stamped text transcripts from audio files. The service parses audio and video files stored in many common formats (WAV, MP3, MP4, AMR, Flac, etc.) and returns a detailed and accurate transcription with timestamps for each word, as well as appropriate capitalized words and punctuation. For most languages, numbers are transcribed into a word form, however for English and German languages Transcribe treats numbers differently depending on the context in which they're used.

Now Transcribe supports 37 languages.

Transcription methods can be divided into two main categories:

  • Batch transcription: transcribing media files that have been uploaded into an Amazon S3 bucket;
  • Streaming transcriptions: Transcribe media streams in real time.

 

Here are some of the features it provides:

  • Single and multi language identification: identifying the dominant language spoken in your media file and creating a transcript. If speakers change language during a conversation, or if each participant speaks a different language, your transcription output correctly detects and transcribes each language;
  • Transcribing multi-channel audio: combines transcriptions from multi channel audio into a single output file. It is possible to enable channel identification for both batch processing and real-time streaming;
  • Speaker diarization: the partition of the text from different speakers, detecting each speaker in the provided audio file;
  • Custom language models: designed to improve transcription accuracy for domain-specific speech. This includes any content that goes beyond the everyday type of conversations. For example, an audio recording of a report from a scientific conference will obviously contain special scientific terms that standard transcription is unlikely to be able to recognize. In this case, you can train a custom language model to recognize the specialized terms used in your discipline;
  • Custom vocabularies: are used to improve transcription accuracy for a list of specific words. These are generally domain-specific terms, such as brand names and acronyms, proper nouns, and words that Amazon Transcribe isn't rendering correctly;
  • Tagging: adding custom metadata to a resource in order to make it easier to identify, organize, and find in a search;
  • Subtitles: can be used to create closed captions for your video and filter inappropriate content from your subtitles.

 

Transcribe offers indispensable features for call centers and support services. It helps to capture useful insights by transcribing customer calls in real time. Analyzing and categorizing calls by keywords, phrases and sentiment can help track negative situations, identify trends in customer issues or allocate calls to specific departments.

It is possible to measure the volume of speech. This metric helps to understand if the customer or employee is talking loudly, which is often an indication of being angry or upset. The quality of communication with the client can also be determined by setting the following metrics: interruptions, non-talk time, talk speed, talk time.

Besides call-centers, Transcribe Service can be useful in almost any field: education, law, e-commerce, and many others. For example, Amazon Comprehend Medical is a machine-learning-powered HIPAA-eligible service pre-trained to identify and extract health data from medical texts, such as prescriptions, procedures, or diagnoses. 

It is difficult to imagine modern technologies without a service that can transform speech into text. And of course, Transcribe has analogues from other digital giants. However, it is worth noting that a large number of developers who have leveraged Amazon service, admit a much higher quality and accuracy compared to similar solutions provided by the current market.