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20242026
most citedRecent Advances in Discrete Speech Tokens: A Review

1 citations · 1 across the 9 of their papers we have counts for

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eess.AS2026

Read What You Hear: Reference-Free Hypotheses Evaluation with Acoustic Discrepancy

Zhihan Li, Hankun Wang, Yiwei Guo +3

Automatic speech recognition systems commonly rely on reference transcriptions for evaluation, while reference-free approaches often depend on internal confidence estimation or aux…

eess.AS2025

AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions

Yiwei Guo, Bohan Li, Hankun Wang +4

Although current large audio language models (LALMs) extend text large language models (LLMs) with generic acoustic understanding abilities, they usually suffer from prompt sensiti…

eess.AS2025

Unlocking Temporal Flexibility: Neural Speech Codec with Variable Frame Rate

Hanglei Zhang, Yiwei Guo, Zhihan Li +3

Most neural speech codecs achieve bitrate adjustment through intra-frame mechanisms, such as codebook dropout, at a Constant Frame Rate (CFR). However, speech segments inherently h…

eess.AS2025★ 1 cited

Recent Advances in Discrete Speech Tokens: A Review

Yiwei Guo, Zhihan Li, Hankun Wang +7

The rapid advancement of speech generation technologies in the era of large language models (LLMs) has established discrete speech tokens as a foundational paradigm for speech repr…

eess.AS2024

Why Do Speech Language Models Fail to Generate Semantically Coherent Outputs? A Modality Evolving Perspective

Hankun Wang, Haoran Wang, Yiwei Guo +3

Although text-based large language models exhibit human-level writing ability and remarkable intelligence, speech language models (SLMs) still struggle to generate semantically coh…

eess.AS2024

LSCodec: Low-Bitrate and Speaker-Decoupled Discrete Speech Codec

Yiwei Guo, Zhihan Li, Chenpeng Du +3

Although discrete speech tokens have exhibited strong potential for language model-based speech generation, their high bitrates and redundant timbre information restrict the develo…

eess.AS2024

vec2wav 2.0: Advancing Voice Conversion via Discrete Token Vocoders

Yiwei Guo, Zhihan Li, Junjie Li +5

We propose a new speech discrete token vocoder, vec2wav 2.0, which advances voice conversion (VC). We use discrete tokens from speech self-supervised models as the content features…