Search papers, labs, and topics across Lattice.
5
0
4
3
Context biasing methods can slash biased word error rates by up to 88%, outperforming speech LLMs in challenging ASR scenarios.
Disfluencies are not just noise; they carry crucial meaning that, when ignored, significantly degrades translation quality.
Personalized fine-tuning of ASR models can reduce word error rates for dysarthric speech to as low as 9.7%, transforming communication for affected individuals.
Speech synthesis can now adaptively enhance clarity and vocal effort, mimicking human responses in noisy environments.
Text prompts might be inflating your SLLM's performance: spoken prompts reveal a significant performance gap, especially in low-resource languages.
