East Asian languages | Smallest AI Docs

East Asian languages - Multi-dataset (Streaming)

WER for the four East Asian languages on the streaming endpoint (US region). Three datasets per language covering read speech (FLEURS), conversational/crowdsourced speech (Common Voice 25), and language-specific corpora (JSUT, Zeroth-Korean, MDCC, AISHELL-1). Compared head-to-head against Deepgram Nova-3. Lower WER is better.

Lang	Dataset	Smallest Pulse	Deepgram Nova 3
Japanese	CV-25	23.84%	34.81%
Japanese	FLEURS	10.78%	17.11%
Japanese	JSUT BASIC5000	11.47%	11.65%
Korean	CV-25	9.79%	9.66%
Korean	FLEURS	7.95%	10.79%
Korean	Zeroth-Korean	5.25%	6.46%
Cantonese	CV-25	6.16%	14.09%
Cantonese	FLEURS	13.06%	15.43%
Cantonese	MDCC	5.85%	12.77%
Mandarin	CV-25	15.99%	22.44%
Mandarin	FLEURS	14.25%	13.89%
Mandarin	AISHELL-1	7.34%	8.69%
Average	-	10.91%	15.50%

Pulse averages 10.91% WER vs Deepgram Nova-3’s 15.50% across the four East Asian languages - Pulse leads on 10 of 12 dataset rows, with the largest gains on Japanese CV-25 and Cantonese CV-25.

These four languages stream from wss://api.us.smallest.ai/waves/v1/stt/live?model=pulse only (US region). See the Pulse model card for the region-routing details.