Working paper / 2026
Multi-condition Impairment Speech-to-Text Bench
Abstract
Multi-condition Impairment Speech-to-Text Bench (MISTT) measures the speech-to-text models that voice agents depend on. Every model hears the same 2,999 frozen clips of voice-agent calls, doctor–patient consultations and five-language parliamentary speech, plus 400 degraded copies of 100 of them: phone lines, low-bitrate codecs, packet loss, background noise and an intelligible background talker. Streaming models are timed the way an agent waits on them, from the forced end of speech to the final transcript. Accuracy carries bootstrap confidence intervals, and the degraded copies are paired with their clean originals, so robustness is measured on the same words.
v0 · October 2026
Alibaba · Streaming · #28 of 36 streaming by English WER · alibaba-fun-asr-realtime-stream
English WER
5.86%
95% CI 5.46% to 6.25%
TTFS p50 / p95
334 ms
p95 423 ms
$ / 1k audio min
$6.20
list $0.0054/min
Δ Severe
+6.3 pts
3.89% → 10.14% on 100 clips
| English index | 5.86% | 5.46% – 6.25% |
| pipecat (voice-agent turns) | 3.04% | 2.74% – 3.34% |
| primock57 (doctor–patient) | 8.68% | 7.95% – 9.39% |
| Multilingual (de/fr/es/it pooled) | — | |
| VoxPopuli English | 7.22% | 6.19% – 8.26% |
English substitutions 2.46%, deletions 2.76%, insertions 0.63% · raw (un-normalized) English WER 23.49% · hallucination 0.27% of clips · empty 0.05% · VoxPopuli CER 4.38%
| p50 | p90 | p95 | p99 | max | |
|---|---|---|---|---|---|
| TTFS | 334 ms | 389 ms | 423 ms | 496 ms | 909 ms |
| TTFT | 443 ms | 502 ms | 631 ms | 899 ms | 2.45 s |
| TTFB | 756 ms | 1.48 s | 1.89 s | 3.25 s | 5.88 s |
| Connection setup | 793 ms | 815 ms | 818 ms | 942 ms | 1.16 s |
English WER@500 ms 5.89% (final 5.86%) · finals before t0 0.0% · fallback finals 0.0% · partial words later rewritten 25.3%
| Mix | WER | Δ pts (95% CI) | Worse | Rank |
|---|---|---|---|---|
| Clean | 3.89% | — | — | #57 |
| Light | 5.29% | +1.4 (+0.5 to +2.4) | 25/100 | #72 |
| Moderate | 9.41% | +5.5 (+3.8 to +7.5) | 50/100 | #48 |
| Severe | 10.14% | +6.3 (+4.1 to +8.4) | 52/100 | #47 |
| Crosstalk | 8.89% | +5.0 (+3.4 to +6.6) | 47/100 | #15 |
Bleed 1.06% of background-talker words · ranks are out of 81 on the subset.
