Speaker Style-Aware Phoneme Anchoring for Improved Cross-Lingual Speech Emotion Recognition
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Abstract (arXiv)
Cross-lingual speech emotion recognition (SER) remains a challenging task due to differences in phonetic variability and speaker-specific expressive styles across languages. Effectively capturing emotion under such diverse conditions requires a framework that can align the externalization of emotions across different speakers and languages. To address this problem, we propose a speaker-style aware phoneme anchoring framework that aligns emotional expression at the phonetic and speaker levels. Our method builds emotion-specific speaker communities via graph-based clustering to capture shared speaker traits. Using these groups, we apply dual-space anchoring in speaker and phonetic spaces to enable better emotion transfer across languages. Evaluations on the MSP-Podcast (English) and BIIC-Podcast (Taiwanese Mandarin) corpora demonstrate improved generalization over competitive baselines and provide valuable insights into the commonalities in cross-lingual emotion representation.
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References · 12
- 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
- 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
- 2023EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animationcited by 142
- 2022FreeVC: Towards High-Quality Text-Free One-Shot Voice Conversioncited by 80
- 2021VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversioncited by 64
- 2018Domain Adversarial for Acoustic Emotion Recognitioncited by 25
- 2019Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)cited by 19
- 2019Semi-Supervised Speech Emotion Recognition with Ladder Networkscited by 9
- 2020Compact Graph Architecture for Speech Emotion Recognitioncited by 9
- 2024Revealing Emotional Clusters in Speaker Embeddings: A Contrastive Learning Strategy for Speech Emotion Recognitioncited by 8
- 2024A Layer-Anchoring Strategy for Enhancing Cross-Lingual Speech Emotion Recognitioncited by 6
- 2024Mouth Articulation-Based Anchoring for Improved Cross-Corpus Speech Emotion Recognitioncited by 1
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