Why We Need Speech to Evaluate Speech Translation

arXiv:2605.28227 · cs.CL · Submitted 2026-05-27 · Read on arXiv

cs.CL

Submitted: 2026-05-27

Updated: 2026-08-30

Code: https://github.com/MaikeZuefle/speechCOMET

Terminology

• Fine-Tuning — 20× in this paper · explained in 5 episodes
• Accuracy — 18× in this paper · explained in 1 episode
• Ablation — 8× in this paper · explained in 1 episode
• Benchmark — 7× in this paper · explained in 2 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Transformer — 4× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Modality Gap — 2× in this paper · explained in 4 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Architectural Adaptation — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Information-Theoretic Framework — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• How to Evaluate Speech Translation with Source-Aware Neural MT Metrics
• Analyzing the relationships between pretraining language, phonetic, tonal, and speaker information in self-supervised speech models
• LoRA: Low-Rank Adaptation of Large Language Models
• [b] = [d] - [t] + [p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic
• Seamless: Multilingual Expressive and Streaming Speech Translation
• Unsupervised Cross-lingual Representation Learning at Scale
• Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation
• Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
• Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs
• Early-Exit and Instant Confidence Translation Quality Estimation
• EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
• Qwen2.5-Omni Technical Report

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