Data Scale, Not Latency, Shapes Cross-Lingual Encoder Transfer in Streaming ASR
Adapting a streaming speech recognition model to a new language requires choosing between two plausible warm starts: a multilingual (ML) encoder or an English-only (EN) encoder. The common intuition is that the multilingual encoder should help most at low data, but it is unclear how long that advantage persists, whether tight streaming latency amplifies it, and whether it survives deployment quantization. We answer these questions with a controlled sweep of a 0.6 B-parameter cache-aware FastConformer transducer across eight European languages, up to five target-language data scales (100 h to 2500 h), three streaming tiers plus offline decoding, and up to four public test sets. The main re...
| Authors | Nenad Banfic |
|---|---|
| Primary category | cs.AI |
| Published | 23 June 2026 |
| Last updated at source | 13 September 2026 |
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