Overview

As voice assistants, chatbots, and AI-driven customer interfaces become more common, ensuring these systems understand and respond appropriately to real human input is critical. Appen USA’s Voice & Natural Language Testing service offers real-world validation of conversational AI systems using a U.S.-based, linguistically diverse workforce.

Our teams test and provide feedback on voice, speech, and natural language interfaces—identifying comprehension gaps, tone mismatches, and inclusion issues before your product reaches customers.

What We Test

• Voice assistants (e.g., Alexa, Siri, Google Assistant)
• Interactive voice response (IVR) systems
• Chatbots and virtual agents
• Speech-to-text accuracy
• Tone, accent, and dialect handling
• Intent and sentiment detection

Human Insight, Real Results

Our testers are trained to simulate real-world use cases—across age groups, regions, and speech patterns—to ensure your AI understands varied inputs accurately. Each scenario is documented and scored using a structured rubric that reflects your goals, whether that’s improved accuracy, reduced friction, or cultural relevance.

Testing includes:

• Scenario simulation (real conversations)
• Accent & dialect challenge sets
• Fail-case documentation
• Response timing audits
• Accessibility evaluation (tone, clarity, speed)

Quality & Security

All testing is conducted by U.S.-based W-2 testers in controlled environments with full nondisclosure protections. Audio files and interactions are securely transmitted and stored, and all user data is anonymized where needed. Testers are given specific scripts, scenarios, and QA frameworks to ensure uniformity.

Why Appen USA?

• Regional language diversity: Testers from across the U.S., capturing real variations
• Compliance-ready protocols: Especially important for health, finance, and public sector tools
• Detailed reporting: You get insights, scoring, and actionable improvements
• Real-human input: No synthetic data—just real-world speech
• Quick ramp-up: Projects can launch in under a week

Proven Results

With our help, clients have:

• Improved NLU accuracy by 27% in the first testing cycle
• Identified over 300 new edge cases across major U.S. regions
• Reduced AI misunderstandings by 41% before public release