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Working paper / 2026

MISTT

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

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Rev AI Machine Streaming

Rev AI · Streaming · #47 of 47 streaming by English WER · revai-machine-stream

English WER

9.67%

95% CI 9.06% to 10.25%

TTFS p50 / p95

169 ms

p95 427 ms

$ / 1k audio min

$6.97

list $0.003333/min

Δ Severe

+15.1 pts

7.41% → 22.52% on 100 clips

Accuracy by dataset

English index9.67%9.06% – 10.25%
pipecat (voice-agent turns)8.30%7.69% – 8.91%
primock57 (doctor–patient)11.04%10.02% – 12.06%
Multilingual (de/fr/es/it pooled)14.43%13.31% – 15.61%
VoxPopuli English15.05%13.78% – 16.14%
VoxPopuli German9.58%8.29% – 10.88%
VoxPopuli French10.54%8.70% – 12.50%
VoxPopuli Spanish14.68%13.06% – 16.41%
VoxPopuli Italian20.89%18.35% – 23.53%

English substitutions 4.32%, deletions 4.07%, insertions 1.27% · raw (un-normalized) English WER 27.38% · hallucination 2.10% of clips · empty 0.17% · VoxPopuli CER 10.09%

Streaming latency

p50p90p95p99max
TTFS169 ms329 ms427 ms751 ms3.03 s
TTFT966 ms1.48 s1.77 s2.38 s6.29 s
TTFB1.38 s2.27 s2.67 s4.28 s7.77 s
Connection setup77 ms96 ms110 ms210 ms281 ms

English WER@500 ms 9.73% (final 9.67%) · finals before t0 1.1% · fallback finals 1.3% · partial words later rewritten 16.1%

Robustness · same 100 clips

MixWERΔ pts (95% CI)WorseRank
Clean7.41%——#100
Light8.93%+1.5 (+0.6 to +2.6)28/100#99
Moderate21.39%+14.0 (+10.2 to +17.8)71/100#102
Severe22.52%+15.1 (+11.2 to +19.4)65/100#98
Crosstalk26.96%+19.6 (+16.3 to +23.4)90/100#86

Bleed 6.85% of background-talker words · ranks are out of 104 on the subset.

Configuration and pricing

Languages
en, de, fr, es, it
Finalize
no flush-without-close: finalize sends EOS, ack = first final after EOS
Rate
$0.003333/min pay-as-you-go · billed on session time · 1 s increments · 15 s minimum
Effective
$6.97 per 1k audio min on this run · clean run cost $2.95
Pricing notes
Rates from rev.ai/pricing (no separate streaming rate); stream billed on max(audio, wall-clock), 1 s rounding, 15 s minimum.
Source
https://docs.rev.ai/api/streaming/billing · checked 2026-10-19
Clip outcomes
ok 2,999