mlsanityData to 14 Oct 2026

MiniSUPERB: Lightweight Benchmark for Self-supervised Speech Models

arXiv 2305.19011 ↗First posted 30 May 2023eess.AS cs.CL cs.LGcited by 8

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Abstract (arXiv)

SUPERB was proposed to evaluate the generalizability of self-supervised learning (SSL) speech models across various tasks. However, it incurs high computational costs due to the large datasets and diverse tasks. In this paper, we introduce MiniSUPERB, a lightweight benchmark that efficiently evaluates SSL speech models with comparable results to SUPERB but lower computational costs significantly. We carefully select representative tasks, sample datasets, and extract model representations offline. Our approach achieves a Spearman's rank correlation of 0.954 and 0.982 with SUPERB Paper and SUPERB Challenge, respectively. Additionally, we reduce the computational cost by 97% in terms of Multiply-ACcumulate operations (MACs). Furthermore, we evaluate SSL speech models in few-shot scenarios and observe significant variations in their performance. To our knowledge, this is the first study to examine both the computational cost of the model itself and the cost of evaluating it on a benchmark.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 24 of its 27 references that are in the map. First posted on arXiv 30 May 2023.

Builds on

24 of 27 references.

References · 24

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  3. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
  4. 2021BEiT: BERT Pre-Training of Image Transformerscited by 2,375
  5. 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
  6. 2018Deep contextualized word representationscited by 2,290
  7. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
  8. 2017VoxCeleb: a large-scale speaker identification datasetcited by 732
  9. 2021SUPERB: Speech processing Universal PERformance Benchmarkcited by 666
  10. 2021Masked Feature Prediction for Self-Supervised Visual Pre-Trainingcited by 576
  11. 2019Libri-Light: A Benchmark for ASR with Limited or No Supervisioncited by 467
  12. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 463
12 more
  1. 2021GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audiocited by 399
  2. 2022Self-Supervised Speech Representation Learning: A Reviewcited by 260
  3. 2019Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoderscited by 198
  4. 2020TERA: Self-Supervised Learning of Transformer Encoder Representation for Speechcited by 188
  5. 2022Compute Trends Across Three Eras of Machine Learningcited by 163
  6. 2020LibriMix: An Open-Source Dataset for Generalizable Speech Separationcited by 155
  7. 2020Unsupervised pretraining transfers well across languagescited by 101
  8. 2019Learning Problem-agnostic Speech Representations from Multiple Self-supervised Taskscited by 87
  9. 2020DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector Quantizationcited by 77
  10. 2022SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilitiescited by 77
  11. 2019Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognitioncited by 66
  12. 2022SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learningcited by 26

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 4; 2026: 1.

8 papers.

  1. 2023SpeechGen: Unlocking the Generative Power of Speech Language Models with Promptscited by 21
  2. 2024DAISY: Data Adaptive Self-Supervised Early Exit for Speech Representation Modelscited by 4
  3. 2025TS-SUPERB: A Target Speech Processing Benchmark for Speech Self-Supervised Learning Modelscited by 4
  4. 2024PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniquescited by 3
  5. 2025Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalizationcited by 2
  6. 2025An Exploration of Mamba for Speech Self-Supervised Modelscited by 2
  7. 2025Multilingual Dataset Integration Strategies for Robust Audio Deepfake Detection: A SAFE Challenge Systemcited by 0
  8. 2026A SUPERB-Style Benchmark of Self-Supervised Speech Models for Audio Deepfake Detectioncited by 0