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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.