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20242026
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eess.AS2026

Probing Neural Audio Codecs with Speaker Traits and Speech Characteristics

Jihwan Lee, Tiantian Feng, Minu Kim +6

Neural audio codecs are increasingly used for low-bitrate speech coding and serve as tokenizers for speech language models, yet it remains unclear how their codebook hierarchies en…

eess.AS2026

ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions

Thomas Thebaud, Junhyeok Lee, Laureano Moro-Velazquez +2

Speaker embeddings, or x-vectors, are widely used to represent speaker identity and speaker-related attributes, but existing embedding extractors are typically descriptive rather t…

eess.AS2025

Improving Test-Time Performance of RVQ-based Neural Codecs

Hyeongju Kim, Junhyeok Lee, Jacob Morton +2

The residual vector quantization (RVQ) technique plays a central role in recent advances in neural audio codecs. These models effectively synthesize high-fidelity audio from a limi…

eess.AS2025

MaskVCT: Masked Voice Codec Transformer for Zero-Shot Voice Conversion With Increased Controllability via Multiple Guidances

Junhyeok Lee, Helin Wang, Yaohan Guan +4

We introduce MaskVCT, a zero-shot voice conversion (VC) model that offers multi-factor controllability through multiple classifier-free guidances (CFGs). While previous VC models r…

eess.AS2025

CapSpeech: Enabling Downstream Applications in Style-Captioned Text-to-Speech

Helin Wang, Jiarui Hai, Dading Chong +11

Recent advancements in generative artificial intelligence have significantly transformed the field of style-captioned text-to-speech synthesis (CapTTS). However, adapting CapTTS to…