Open navigation

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

← All models
ZO

Zoom Scribe Live

Zoom · Streaming · #14 of 36 streaming by English WER · zoom-scribe-live-stream

English WER

4.27%

95% CI 3.91% to 4.63%

TTFS p50 / p95

236 ms

p95 345 ms

$ / 1k audio min

$3.61

list $0.00333/min

Δ Severe

+3.1 pts

2.76% → 5.85% on 100 clips

Accuracy by dataset

English index4.27%3.91% – 4.63%
pipecat (voice-agent turns)2.28%2.07% – 2.53%
primock57 (doctor–patient)6.26%5.59% – 6.96%
Multilingual (de/fr/es/it pooled)11.23%10.22% – 12.29%
VoxPopuli English5.44%4.58% – 6.31%
VoxPopuli German11.51%10.11% – 13.08%
VoxPopuli French10.82%8.94% – 12.75%
VoxPopuli Spanish7.84%6.40% – 9.43%
VoxPopuli Italian15.02%12.54% – 17.68%

English substitutions 1.66%, deletions 1.41%, insertions 1.20% · raw (un-normalized) English WER 17.06% · hallucination 1.84% of clips · empty 0.07% · VoxPopuli CER 7.38%

Streaming latency

p50p90p95p99max
TTFS236 ms316 ms345 ms430 ms624 ms
TTFT6.05 s12.86 s15.50 s23.08 s30.53 s
TTFB386 ms1.10 s1.38 s2.59 s5.70 s
Connection setup465 ms546 ms571 ms625 ms2.41 s

English WER@500 ms 4.27% (final 4.27%) · finals before t0 0.0% · fallback finals 0.0% · partial words later rewritten 0.0%

Robustness · same 100 clips

MixWERΔ pts (95% CI)WorseRank
Clean2.76%——#32
Light4.13%+1.4 (+0.6 to +2.3)27/100#51
Moderate5.17%+2.4 (+1.5 to +3.6)38/100#13
Severe5.85%+3.1 (+1.9 to +4.5)41/100#13
Crosstalk5.25%+2.5 (+1.2 to +3.8)36/100#2

Bleed 0.42% of background-talker words · ranks are out of 81 on the subset.

Configuration and pricing

Languages
en, de, fr, es, it
Finalize
session.close drains the pending turn; ack = session.closed
Config notes
Live mode picks the model from the locale (en-US -> zoom-scribe-en, logged in session info); no model field.
Rate
$0.00333/min pay-as-you-go · billed on audio time
Effective
$3.61 per 1k audio min on this run · clean run cost $1.53
Pricing notes
Zoom does not publish Scribe Live rates; AA's Zoom Scribe figure ($3.33/1k min) used as a placeholder. Confirm in Platform Studio billing.
Source
https://artificialanalysis.ai/speech-to-text/models/zoom-scribe · checked 2026-10-19
Clip outcomes
ok 2,999