Validate IVR flows, voice bots, and speech recognition accuracy across accents, noise conditions, and edge-case intents - so your voice product never lets a caller down.
Difference between lab accuracy and real-world noisy-call accuracy our audits uncover.
EN-US, EN-IN, EN-GB, EN-AU, ES-MX, FR-FR, DE-DE and more included in coverage plans.
Automated scenario execution across DTMF, speech, intent routing, and escalation paths.
Most voice failures aren't caught in the lab - they surface in noisy environments, with non-native speakers, or mid-flow when the user says something the bot didn't train on. We find them before your callers do.
The speech engine transcribes "cancel my order" as "cancel my border" in a café environment, routing the caller to immigration services. We stress-test every intent against 6 background noise profiles and 4+ accent groups.
A 3-second silence due to network jitter forces escalation to an agent queue — at 2× the cost. We validate every timeout threshold against realistic connection conditions, including mobile data latency spikes.
Account numbers with 16+ digits get clipped mid-read by the TTS engine, leaving callers confused and repeating themselves. We run TTS assertion tests on every dynamic prompt template, not just the happy-path samples.
Hold music frequency bleeds into the DTMF band, causing tones to drop. This is a classic telco edge case — we simulate PSTN, SIP, and WebRTC call paths to catch interference before it reaches production.
One testing framework doesn't cover the full voice stack. We match the right tool to the right layer - from PSTN simulation and ASR benchmarking to IVR flow automation and TTS assertion.
End-to-end IVR and contact centre test automation. We build test scripts for every call flow, regression-test prompt changes, and verify DTMF + speech paths across trunk groups.
We benchmark ASR accuracy across engines - comparing word error rate (WER) for your specific vocabulary, domain terms, and target demographics before you commit to an engine.
We simulate realistic call conditions: PSTN jitter, background café noise, hold music DTMF bleed, and mobile codec degradation. Real-world SNR profiles, not lab-clean WAV files.
For conversational AI and voice bots, we validate intent recognition rates, entity extraction accuracy, and fallback behaviour when the bot doesn't understand an utterance.
Mobile voice features - push-to-talk, in-app voice commands, voice search - are tested with Appium on real devices and Espresso for Android. Voice permissions, mic access, and UI state all verified.
Every test run publishes ASR accuracy by accent, per-scenario pass/fail, WER trends, and noise-resilience scores - all linked from your CI pipeline so regressions are visible at merge time.
Pick a scenario below - the simulator replays a real voice utterance, streams the ASR transcript, and flags every defect the moment it's detected. This is exactly what runs inside your CI pipeline.
A voice product that scores 96% accuracy in a studio is a different product from the one your users experience. We test the gap - every accent, every noise floor.
Voice QA is not manual call listening. It's structured test automation, acoustic profiling, and regression coverage - integrated into your sprint cadence.
Common questions about how a voice testing engagement with us actually runs.
Thirty minutes, no deck. Bring one call recording or IVR flow definition - we'll identify the three most likely failure points and what we'd fix first, whether or not you hire us.
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