mlsanityData to 7 Oct 2026

Codec-SUPERB: An In-Depth Analysis of Sound Codec Models

arXiv 2402.13071 ↗First posted 20 Feb 2024eess.AS cs.SDcited by 25

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Abstract (arXiv)

The sound codec's dual roles in minimizing data transmission latency and serving as tokenizers underscore its critical importance. Recent years have witnessed significant developments in codec models. The ideal sound codec should preserve content, paralinguistics, speakers, and audio information. However, the question of which codec achieves optimal sound information preservation remains unanswered, as in different papers, models are evaluated on their selected experimental settings. This study introduces Codec-SUPERB, an acronym for Codec sound processing Universal PERformance Benchmark. It is an ecosystem designed to assess codec models across representative sound applications and signal-level metrics rooted in sound domain knowledge.Codec-SUPERB simplifies result sharing through an online leaderboard, promoting collaboration within a community-driven benchmark database, thereby stimulating new development cycles for codecs. Furthermore, we undertake an in-depth analysis to offer insights into codec models from both application and signal perspectives, diverging from previous codec papers mainly concentrating on signal-level comparisons. Finally, we will release codes, the leaderboard, and data to accelerate progress within the community.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2024.

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Citing papers per year: 2024: 3; 2025: 17; 2026: 5.

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  1. 2025On The Landscape of Spoken Language Models: A Comprehensive Surveycited by 116
  2. 2025Recent Advances in Discrete Speech Tokens: A Reviewcited by 42
  3. 2025M-Prometheus: A Suite of Open Multilingual LLM Judgescited by 37
  4. 2024DASB - Discrete Audio and Speech Benchmarkcited by 32
  5. 2025ViSAGe: Video-to-Spatial Audio Generationcited by 11
  6. 2025Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Modelcited by 7
  7. 2025Fake-Mamba: Real-Time Speech Deepfake Detection Using Bidirectional Mamba as Self-Attention's Alternativecited by 6
  8. 2025Unlocking Temporal Flexibility: Neural Speech Codec with Variable Frame Ratecited by 4
  9. 2025Robust and Efficient Autoregressive Speech Synthesis with Dynamic Chunk-wise Prediction Policycited by 4
  10. 2025Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoderscited by 4
  11. 2024EnCLAP++: Analyzing the EnCLAP Framework for Optimizing Automated Audio Captioning Performancecited by 3
  12. 2025Codec2Vec: Self-Supervised Speech Representation Learning Using Neural Speech Codecscited by 3
13 more
  1. 2025Analysing the Language of Neural Audio Codecscited by 2
  2. 2026Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steeringcited by 2
  3. 2024Expanding on EnCLAP with Auxiliary Retrieval Model for Automated Audio Captioningcited by 1
  4. 2025Towards Efficient Speech-Text Jointly Decoding within One Speech Language Modelcited by 1
  5. 2025Benchmarking Prosody Encoding in Discrete Speech Tokenscited by 1
  6. 2025Pseudo2Real: Task Arithmetic for Pseudo-Label Correction in Automatic Speech Recognitioncited by 1
  7. 2026Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codeccited by 1
  8. 2026TiCo: Time-Controllable Spoken Dialogue Modelcited by 1
  9. 2026Language-Statistical Analysis of Neural Audio Codec Tokens Across Architectures, Corpora, and Noise Conditionscited by 1
  10. 2025Towards Generalized Source Tracing for Codec-Based Deepfake Speechcited by 0
  11. 2025Task-Specific Audio Coding for Machines: Machine-Learned Latent Features Are Codes for That Machinecited by 0
  12. 2025FuseCodec: Semantic-Contextual Fusion and Supervision for Neural Codecscited by 0
  13. 2026Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignmentcited by 0