Speech-to-text systems break down first at the edges. Regional accents. Non-native speakers. Fast talkers. Pauses. Interruptions. Background noise. If your STT only works for one speaking style, it does not work in production.
Cekura lets you test how your STT performs across real accent and dialect variation before users find the gaps.
Test real accents, not idealized audio
Run the same conversations across predefined and custom personalities that reflect how people actually speak. Indian-accent English. Non-native fluency. Hesitations. Overlapping speech. Environmental noise. You can also create your own accent or dialect profiles to match your audience exactly.
Testing is scenario-driven, not dataset-driven. Every call is a full conversation, not a clipped audio sample.
Measure what breaks STT in practice
Each simulation automatically generates transcripts and evaluates speech quality and flow, including pronunciation accuracy, letter-level pronunciation errors, interruptions, silence, latency, talk ratio, pitch, clarity, sentiment, and task success. Failures are timestamped so you can hear the exact moment recognition drifted.
If you need deeper accuracy analysis, export transcripts and metadata to compute accent-specific WER, CER, or custom subgroup metrics using Python. The raw data is there.
Compare fairness across accents and speaking styles
Run identical scenarios across different accents, genders, and language styles. Compare outcomes side by side. Spot where instruction following, comprehension, or task completion degrades for certain speakers. Bias and stress scenarios help surface uneven behavior before it reaches real users.
Test multilingual and mixed-language conversations
Configure agents in different languages and replay the same workflows across them. Simulate code-switching by mixing languages within a single conversation. This is especially useful for global support and diaspora audiences.
Scale without limits
There is no fixed corpus size. Generate hundreds or thousands of calls per accent, noise condition, or workflow. Load test STT behavior under concurrency. Re-run tests automatically on every model, prompt, or infrastructure change.
Built for production teams
Cekura integrates with major voice and chat stacks, runs in CI pipelines, and sends alerts when accent-specific performance drifts. Audio and transcripts can be redacted, with enterprise-grade security and compliance built in.
If your STT needs to work for everyone who calls, you need to test everyone who calls.
Cekura is the voice and chat testing platform teams use to validate accent and dialect coverage before production and continuously after launch.