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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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Scribe v2 Realtime

ElevenLabs · Streaming · #20 of 47 streaming by English WER · elevenlabs-scribe-v2-realtime-stream

English WER

4.55%

95% CI 4.23% to 4.88%

TTFS p50 / p95

139 ms

p95 203 ms

$ / 1k audio min

$7.05

list $0.0065/min

Δ Severe

+7.5 pts

2.80% → 10.30% on 100 clips

Accuracy by dataset

English index4.55%4.23% – 4.88%
pipecat (voice-agent turns)3.31%3.05% – 3.57%
primock57 (doctor–patient)5.79%5.12% – 6.46%
Multilingual (de/fr/es/it pooled)13.21%12.17% – 14.44%
VoxPopuli English7.51%6.46% – 8.55%
VoxPopuli German12.90%11.56% – 14.43%
VoxPopuli French10.96%9.18% – 13.01%
VoxPopuli Spanish8.93%7.08% – 11.16%
VoxPopuli Italian20.04%17.48% – 22.63%

English substitutions 1.78%, deletions 0.85%, insertions 1.92% · raw (un-normalized) English WER 16.65% · hallucination 3.47% of clips · empty 0.03% · VoxPopuli CER 8.91%

Streaming latency

p50p90p95p99max
TTFS139 ms186 ms203 ms386 ms1.71 s
TTFT1.78 s2.08 s2.11 s2.14 s6.46 s
TTFB2.11 s2.18 s2.27 s4.02 s6.96 s
Connection setup98 ms156 ms160 ms248 ms2.23 s

English WER@500 ms 8.48% (final 4.55%) · finals before t0 0.0% · fallback finals 0.0% · partial words later rewritten 14.5%

Robustness · same 100 clips

MixWERΔ pts (95% CI)WorseRank
Clean2.80%——#44
Light3.45%+0.6 (+0.1 to +1.3)17/100#47
Moderate7.61%+4.8 (+2.9 to +6.7)38/100#43
Severe10.30%+7.5 (+4.6 to +10.9)41/100#58
Crosstalk12.30%+9.5 (+5.9 to +13.2)46/100#41

Bleed 2.37% of background-talker words · ranks are out of 104 on the subset.

Configuration and pricing

Languages
en, de, fr, es, it
Finalize
commit: true; ack = next committed_transcript
Config notes
manual commit: only our commit at the shared VAD speech end produces the final (plus auto-commits on very long audio).
Rate
$0.0065/min pay-as-you-go · billed on audio time
Effective
$7.05 per 1k audio min on this run · clean run cost $2.98
Pricing notes
Billed per audio minute; partial-minute rounding not published.
Source
https://elevenlabs.io/pricing/api · checked 2026-10-19
Clip outcomes
ok 2,999