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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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Alebex STT Realtime

Alebex · Streaming · #23 of 47 streaming by English WER · alebex-stt-realtime-stream

English WER

4.71%

95% CI 4.12% to 5.36%

TTFS p50 / p95

125 ms

p95 296 ms

$ / 1k audio min

$2.17

list $0.002/min

Δ Severe

+6.6 pts

2.48% → 9.10% on 100 clips

Accuracy by dataset

English index4.71%4.12% – 5.36%
pipecat (voice-agent turns)1.93%1.68% – 2.25%
primock57 (doctor–patient)7.48%6.36% – 8.69%
Multilingual (de/fr/es/it pooled)14.82%13.44% – 16.22%
VoxPopuli English7.43%6.21% – 8.69%
VoxPopuli German14.90%11.93% – 18.66%
VoxPopuli French12.53%10.43% – 14.92%
VoxPopuli Spanish9.76%7.95% – 11.73%
VoxPopuli Italian22.26%19.09% – 25.32%

English substitutions 1.66%, deletions 2.47%, insertions 0.58% · raw (un-normalized) English WER 20.07% · hallucination 2.50% of clips · empty 1.23% · VoxPopuli CER 9.87%

Streaming latency

p50p90p95p99max
TTFS125 ms207 ms296 ms445 ms1.03 s
TTFT405 ms458 ms543 ms949 ms6.78 s
TTFB613 ms1.33 s1.62 s2.81 s5.92 s
Connection setup253 ms256 ms257 ms264 ms1.26 s

English WER@500 ms 4.71% (final 4.71%) · finals before t0 0.0% · fallback finals 0.0% · partial words later rewritten 6.9%

Robustness · same 100 clips

MixWERΔ pts (95% CI)WorseRank
Clean2.48%——#24
Light2.84%+0.4 (−0.1 to +0.9)11/100#24
Moderate8.61%+6.1 (+3.9 to +8.9)43/100#55
Severe9.10%+6.6 (+4.2 to +9.4)42/100#50
Crosstalk7.73%+5.2 (+2.9 to +8.0)44/100#17

Bleed 0.76% of background-talker words · ranks are out of 104 on the subset.

Configuration and pricing

Languages
en, de, fr, es, it
Finalize
{"type":"end"}; ack = the final after it
Rate
$0.002/min pay-as-you-go · billed on audio time
Effective
$2.17 per 1k audio min on this run · clean run cost $0.92
Pricing notes
Prepaid balance; first hour free on new accounts. Billing increment not published.
Source
https://www.alebex.ai/models-developer-accounts · checked 2026-10-19
Clip outcomes
ok 2,999