Diversity Dilemma
In the ever-evolving landscape of customer service, the need to connect with diverse audiences is more critical than ever. At MIST Global, we’re on a mission to explore the nuances of communication by leveraging the power of AWS.
Understanding the Diversity Dilemma
Communication knows no bounds, but linguistic diversity can pose challenges. Picture this: a customer from the loud and colorful streets of Mumbai conversing with an automated system designed to cater to an American accent. They explain their issue to the system, but the automation is not made to work with the accent, so it misunderstands, or worse yet, puts you through a never-ending loop of questions. How can businesses bridge this gap and ensure that their services are accessible to a broader spectrum of customers?
We’ve set out to unravel the intricacies of dialects and accents by engaging volunteers from different states of India. Our approach involves a toll-free number, Amazon Lex, and Lambda functions, forming a comprehensive system to assess the efficiency of Interactive Voice Response (IVR) systems across diverse linguistic landscapes.
The Journey Unfolds
Volunteers from India dial our toll-free number and are greeted by Amazon Connect. The system will ask the volunteers to identify their state so that we can see how much the system can understand people from different states. Once the state is identified, the real test begins. Volunteers repeat 5 sentences prompted by Amazon Lex, allowing us to capture and analyze the transcriptions. It’s not just about understanding what the system hears but delving deeper into how different accents and dialects are interpreted by Amazon Lex.
Decoding the Data with Lambda Functions
The magic happens behind the scenes with our Lambda functions. We take the transcriptions provided by Lex and subject them to a scoring mechanism. This mechanism evaluates each session with a score ranging from 0 to 5, which reflects the efficiency of the IVR system in understanding the spoken words.
At its core, the Lambda function evaluates the similarity between the original sentence and what Lex comprehends. A score of 5 signifies a flawless interpretation, while a lower score indicates room for improvement. This process allows us to gauge the adaptability of IVR systems to diverse linguistic landscapes.
Data Visualization
As we embark on this journey to comprehend the intricacies of dialects and accents, the differentiation among states emerges as a crucial factor. We introduce a compelling visual element to illuminate the disparities—graphical representations of how the scores vary between different states. Our commitment to transparency extends beyond the technical realm; it’s about sharing insights that can revolutionize how businesses connect with customers across diverse linguistic landscapes.
Unlocking Opportunities for Businesses
Now, let’s talk about the broader implications. As businesses strive to connect with a global audience, understanding diverse dialects becomes a strategic imperative. By embracing the need to improve our technology to stay afloat in our interconnected world, companies can refine their customer service experiences to cater to a broader range of accents and linguistic nuances. Businesses can use our solutions to compare scores of different speech recognition and IVR solutions in their workflow and create dashboards to provide useful insights about the efficiency and accuracy.
Embracing Diversity for a Connected Future
In the realm of customer service, adaptation is key. Our project serves as a testament to the possibilities that emerge when technology aligns with the diverse tapestry of human expression. The journey to understanding and embracing different dialects isn’t just a project; it’s a commitment to building a future where businesses truly connect with every customer they serve.
The future of customer engagement is diverse, dynamic, and distinctly human.
In the ever-evolving landscape of customer service, the need to connect with diverse audiences is more critical than ever. At MIST Global, we’re on a mission to explore the nuances of communication by leveraging the power of AWS.
Understanding the Diversity Dilemma
Communication knows no bounds, but linguistic diversity can pose challenges. Picture this: a customer from the loud and colorful streets of Mumbai conversing with an automated system designed to cater to an American accent. They explain their issue to the system, but the automation is not made to work with the accent, so it misunderstands, or worse yet, puts you through a never-ending loop of questions. How can businesses bridge this gap and ensure that their services are accessible to a broader spectrum of customers?
We’ve set out to unravel the intricacies of dialects and accents by engaging volunteers from different states of India. Our approach involves a toll-free number, Amazon Lex, and Lambda functions, forming a comprehensive system to assess the efficiency of Interactive Voice Response (IVR) systems across diverse linguistic landscapes.
Decoding Diversity: Benchmarking AWS Lex Across Indian Dialects
Imagine a world where AI assistants understand the richness and nuance of regional languages. We’re at the forefront of making that a reality with our Proof of Concept (system) exploring the language processing capabilities of AWS Lex across diverse Indian dialects. Buckle up for a journey into the fascinating intersection of technology and linguistics!
Why Benchmarking Dialects Matters:
India, a land of vibrant languages and cultures, presents a unique challenge for AI. With 22 official languages and countless dialects, ensuring inclusivity in conversational AI requires going beyond generic understanding. That’s where our system comes in. We aim to assess how well AWS Lex comprehends user input in various Indian dialects. This data will be crucial for refining Lex’s performance and paving the way for truly inclusive AI interactions.
The Architecture:
Think of our system as a symphony with three key instruments:
- AWS Connect Service: This is a robust contact center solution from Amazon. Users simply call a dedicated phone number to start on the dialect experiment.
- User Interaction Flow: The users repeat a series of pre-defined sentences. This controlled environment allows us to isolate and analyze Lex’s comprehension accuracy.
- Custom Algorithm: Our algorithm analyzes user responses against the actual text, assigning scores for accuracy and effectiveness.
Visualizing Insights with QuickSight:
As we embark on this journey to comprehend the intricacies of dialects and accents, the differentiation among states emerges as a crucial factor. How do we visualize this insight? Enter QuickSight! With this powerful BI tool, we introduce a compelling visual element to illuminate the disparities—graphical representations of how the scores vary between different states. We can readily identify which dialects pose challenges for Lex, pinpoint areas for improvement, and track progress over time.
The Impact Beyond the system:
The implications of this system extend far beyond our company walls. Imagine AI-powered services that seamlessly interact with customers in their native dialects, regardless of location. Healthcare information delivered in familiar tongues, educational resources tailored to regional accents – the possibilities are endless.
Our system is a small step towards a future where language becomes a bridge, not a barrier. By unlocking the power of diversity in AI, we empower communities, promote inclusivity, and ultimately, bring people closer together.
