Žebříček převodu mongolské řeči na text

Porovnejte míru chybovosti slov, rychlost a cenu poskytovatelů převodu řeči na text pro mongolštinu. Každé číslo je změřené na reálném mongolském zvuku — ne marketing.

Datasets used

Public speech corpora used for every provider run. Open a source URL for the upstream dataset card, license, and download.

Common Voice 24 (MN)›https://huggingface.co/datasets/btsee/common-voices-24-mn
Shunya Labs Mongolian Speech›https://huggingface.co/datasets/shunyalabs/mongolian-speech-dataset
Common Voice 20 (MN)›https://huggingface.co/datasets/warmestman/common-voice-20-mn-normalized
Modern Voice›Recorded first-party for this benchmark — audio not distributed, metrics only.

WER vs. rychlost

Každý bod je jeden poskytovatel. Ideální místo je vpravo dole (málo chyb, rychle). Změřeno na reálném mongolském zvuku.

Google STTDuudlaga FlowSpeechmaticsChimegeOpenAI WhisperGPT-4o TranscribeAzure SpeechGladiaGemma 4Whisper large-v3Whisper large-v3-turboWhisper large-v2 MNSeamlessM4T v2MMS-1B-allMoonshine MNwav2vec2 XLSR-53 MNWhisper turbo MNWhisper medium MNElevenLabs Scribe v1ElevenLabs Scribe v2Qwen3-ASR-FlashDolphin smallOmniASR CTC-1BOmniASR LLM-1BVibeVoice ASRWhisper large-v3 MN

Srovnání poskytovatelů

Seřaďte libovolný sloupec. Klikněte na Podrobnosti pro rozpad po vzorcích, ceny a metodiku poskytovatele.

Open source

Poskytovatel	WER ↑	CER	Přesnost	Rychlost	Latence	Cena / 1000 min
Speechmatics	14.4%	7.4%	85.6%	0.51×	13.8s	$8.5	Podrobnosti
Duudlaga FlowNáš	14.6%	7.6%	85.4%	1.47×	5.2s	$19.4	Podrobnosti
Chimege	14.6%	6.6%	85.4%	1.51×	4.7s	$11.1	Podrobnosti
Google STT	16.9%	7.4%	83.1%	1.98×	3.7s	$16	Podrobnosti
Whisper large-v2 MN	20.7%	8.3%	79.3%	0.53×	13.5s	$0	Podrobnosti
Azure Speech	20.8%	9.7%	79.2%	0.39×	17.3s	$16.7	Podrobnosti
Whisper medium MNOverlap	22.5%	8.9%	77.5%	2.7×	2.7s	$0	Podrobnosti
SeamlessM4T v2	24%	11.1%	76%	0.39×	26.3s	$0	Podrobnosti
Whisper turbo MNOverlap	25.7%	9.2%	74.3%	2.43×	3.0s	$0	Podrobnosti
ElevenLabs Scribe v1	27.1%	10.8%	72.9%	2.14×	3.3s	$6.7	Podrobnosti
ElevenLabs Scribe v2	27.1%	10.6%	72.9%	1.51×	4.7s	$3.7	Podrobnosti
Gemma 4	30.2%	14.7%	69.8%	1×	7.3s	$0	Podrobnosti
OmniASR LLM-1B	33.8%	14.2%	66.2%	0.27×	26.6s	$0	Podrobnosti
Whisper large-v3 MNOverlap	39.4%	14.9%	60.6%	1.57×	4.5s	$0	Podrobnosti
MMS-1B-all	41.7%	12.3%	58.3%	19.2×	0.4s	$0	Podrobnosti
wav2vec2 XLSR-53 MNOverlap	45%	16.4%	55%	42.32×	0.2s	$0	Podrobnosti
Dolphin small	49.1%	19.2%	50.9%	1.73×	4.1s	$0	Podrobnosti
OmniASR CTC-1B	51.2%	15.5%	48.8%	0.6×	11.7s	$0	Podrobnosti
GPT-4o Transcribe	53%	27.6%	47%	2.11×	3.7s	$6	Podrobnosti
Moonshine MNOverlap	58.8%	45.2%	41.2%	8.44×	0.8s	$0	Podrobnosti
Whisper large-v3	89.5%	37.4%	10.5%	1.29×	6.0s	$0	Podrobnosti
Gladia	90.1%	38.9%	9.9%	0.75×	9.4s	$10.2	Podrobnosti
Whisper large-v3-turbo	99%	54.4%	1%	0.91×	8.7s	$0	Podrobnosti
Qwen3-ASR-Flash	103.7%	86.4%	-3.7%	2.19×	3.2s	$2.1	Podrobnosti
OpenAI Whisper	105.2%	63.7%	-5.2%	1.5×	4.5s	$6	Podrobnosti
VibeVoice ASR	107%	61%	-7%	0.53×	12.1s	$0	Podrobnosti
Gemini Flash	Benchmark již brzy

Všechny výsledky jsou změřené na reálných mongolských datasetech. Rychlost je × reálný čas (vyšší = rychlejší). Nižší WER je lepší.

Overlap— Models with this badge were trained on data that overlaps the benchmark corpora (Mongolian Common Voice — 113 of 173 samples — or the public Shunya Labs corpus). Scores on overlapping corpora are inflated by memorization; judge these models by the per-dataset table on their details page, especially the corpora they were NOT trained on.

Duudlaga Voice Set

92 samples · 10.2 min · 28 systems

A second corpus recorded first-party for this benchmark, covering what the public Mongolian datasets barely contain: modern loanwords, English/Mongolian code-switching, numbers, dates, and commands. Every system is measured on the same 92 recordings.

Poskytovatel	WER	CER	Přesnost	Rychlost
1Duudlaga FlowNáš	9.5%	5.3%	90.5%	1.27×
2Google STT	11.7%	5.5%	88.3%	2.28×
3Chimege	14.5%	6.8%	85.5%	1.48×
4Speechmatics	15.3%	7.6%	84.7%	0.5×
5Gemini 3.5 Flash	19.5%	11.4%	80.5%	0.06×
6SeamlessM4T v2Open source	22.9%	10.4%	77.1%	4.32×
7Whisper large-v2 MNOpen source	23.2%	10.9%	76.8%	0.55×
8ElevenLabs Scribe v1	23.4%	9.3%	76.6%	2.09×
9ElevenLabs Scribe v2	24.6%	9.8%	75.4%	1.47×
10Azure Speech	26.1%	10.9%	73.9%	0.32×
11Gemma 4Open source	27.7%	13.2%	72.3%	1.04×
12OmniASR LLM-1BOpen source	34.5%	14.5%	65.5%	0.27×
13Whisper medium MNOpen sourceOverlap	35.1%	14.8%	64.9%	2.71×
14Whisper turbo MNOpen sourceOverlap	37.6%	14.1%	62.4%	2.59×
15Whisper large-v3 MNOpen sourceOverlap	41%	17.1%	59%	1.58×
16GPT-4o Transcribe	44.3%	23.7%	55.7%	2.62×
17MMS-1B-allOpen source	45.3%	15.1%	54.7%	20.52×
18Dolphin smallOpen source	46.1%	19%	53.9%	1.69×
19W2v-BERT 2.0 MNOpen sourceOverlap	46.3%	18.2%	53.7%	28.12×
20OmniASR CTC-1BOpen source	54.9%	18.9%	45.1%	0.59×
21wav2vec2 XLSR-53 MNOpen sourceOverlap	56.3%	23.9%	43.7%	45.7×
22Whisper large-v3Open source	87.3%	36.6%	12.7%	1.55×
23Gladia	88.1%	39.9%	11.9%	0.74×
24Moonshine MNOpen sourceOverlap	96.2%	75.7%	3.8%	8.36×
25Whisper large-v3-turboOpen source	98.1%	57.1%	1.9%	1.19×
26Qwen3-ASR-Flash	103.6%	89.9%	-3.6%	2.07×
27OpenAI Whisper	104.6%	63.8%	-4.6%	1.32×
28VibeVoice ASROpen source	110.1%	64%	-10.1%	0.4×

Recorded first-party for this benchmark — audio not distributed, metrics only.