Does Translation-Enhanced Speech Encoder Pre-training Affect Speech LLMs?
Connecting a pre-trained speech encoder to a Large Language Model (LLM) is the standard architecture for building Speech LLMs. However, a structural misalignment exists between the encoder and the LLM. Unlike encoders based on automatic speech recognition, which often produce representations in separate language-specific spaces, LLMs operate within a unified language-agnostic space. A mechanism is required to align the encoder's language-specific representations with the LLM's shared space. We argue that speech translation provides a principled way to achieve this. Unlike monolingual transcription, translation requires the model to bridge different languages and learn language-agnostic re...
| Authors | Tomoya Mizumoto, Yusuke Fujita |
|---|---|
| Primary category | eess.AS |
| Published | 24 June 2026 |
| Last updated at source | 24 June 2026 |
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