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Towards Interpretable Framework for Neural Audio Codecs via Sparse Autoencoders: Exploration toward Age, Gender, and Accent Steering
Shih-Heng Wang, Tiantian Feng, Aditya Kommineni +4
Neural audio codecs (NACs) are widely used in speech generation and audio-language modeling, yet how they encode speaker-trait information remains poorly understood. Prior work app…
Towards Interpretable Framework for Neural Audio Codecs via Sparse Autoencoders: A Case Study on Accent Information
Shih-Heng Wang, Tiantian Feng, Aditya Kommineni +4
Neural Audio Codecs (NACs) are widely adopted in modern speech systems, yet how they encode linguistic and paralinguistic information remains unclear. Improving the interpretabilit…
Speech Codec Probing from Semantic and Phonetic Perspectives
Xuan Shi, Chang Zeng, Tiantian Feng +3
Speech tokenizers are essential for connecting speech to large language models (LLMs) in multimodal systems. Speech tokenizers are expected to preserve both semantic and acoustic i…
Do Neural Codecs Generalize? A Controlled Study Across Unseen Languages and Non-Speech Tasks
Shih-Heng Wang, Jiatong Shi, Jinchuan Tian +2
This paper investigates three crucial yet underexplored aspects of the generalization capabilities of neural audio codecs (NACs): (i) whether NACs can generalize to unseen language…