mlsanityData to 7 Oct 2026

Efficient Parallel Audio Generation using Group Masked Language Modeling

arXiv 2401.01099 ↗First posted 2 Jan 2024eess.AS cs.AI cs.LGcited by 5

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Abstract (arXiv)

We present a fast and high-quality codec language model for parallel audio generation. While SoundStorm, a state-of-the-art parallel audio generation model, accelerates inference speed compared to autoregressive models, it still suffers from slow inference due to iterative sampling. To resolve this problem, we propose Group-Masked Language Modeling~(G-MLM) and Group Iterative Parallel Decoding~(G-IPD) for efficient parallel audio generation. Both the training and sampling schemes enable the model to synthesize high-quality audio with a small number of iterations by effectively modeling the group-wise conditional dependencies. In addition, our model employs a cross-attention-based architecture to capture the speaker style of the prompt voice and improves computational efficiency. Experimental results demonstrate that our proposed model outperforms the baselines in prompt-based audio generation.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 32 of its 33 references that are in the map. First posted on arXiv 2 Jan 2024.

Builds on

32 of 33 references.

References · 32

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20 more
  1. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,139
  2. 2022MaskGIT: Masked Generative Image Transformercited by 1,082
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  16. 2023SoundStorm: Efficient Parallel Audio Generationcited by 111
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 1.

5 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
  2. 2024Accelerating Codec-based Speech Synthesis with Multi-Token Prediction and Speculative Decoding
  3. 2026An Efficient vLLM-Based Inference Pipeline for Unified Audio Understanding and Generation
  4. 2025Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
  5. 2025Continuous Audio Language Models
  6. 2026UNISON: A Unified Sound Generation and Editing Framework via Deep LLM Fusion
  7. 2026Fast Text-to-Audio Generation with One-Step Sampling via Energy-Scoring and Auxiliary Contextual Representation Distillation ↗
  8. 2024TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization