mlsanityData to 7 Oct 2026

Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation

arXiv 2007.13465 ↗First posted 27 Jul 2020eess.AS cs.LG cs.SDcited by 43

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Abstract (arXiv)

We propose a self-supervised representation learning model for the task of unsupervised phoneme boundary detection. The model is a convolutional neural network that operates directly on the raw waveform. It is optimized to identify spectral changes in the signal using the Noise-Contrastive Estimation principle. At test time, a peak detection algorithm is applied over the model outputs to produce the final boundaries. As such, the proposed model is trained in a fully unsupervised manner with no manual annotations in the form of target boundaries nor phonetic transcriptions. We compare the proposed approach to several unsupervised baselines using both TIMIT and Buckeye corpora. Results suggest that our approach surpasses the baseline models and reaches state-of-the-art performance on both data sets. Furthermore, we experimented with expanding the training set with additional examples from the Librispeech corpus. We evaluated the resulting model on distributions and languages that were not seen during the training phase (English, Hebrew and German) and showed that utilizing additional untranscribed data is beneficial for model performance.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2020.

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Citing papers per year: 2021: 10; 2022: 12; 2023: 12; 2024: 3; 2025: 2; 2026: 4.

43 papers.

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  1. 2022AudioGen: Textually Guided Audio Generationcited by 292
  2. 2021Speech Resynthesis from Discrete Disentangled Self-Supervised Representationscited by 243
  3. 2021Unsupervised Speech Recognitioncited by 147
  4. 2022Efficient Transformers with Dynamic Token Poolingcited by 75
  5. 2023What Do Self-Supervised Speech Models Know About Words?cited by 62
  6. 2023Analysing Discrete Self Supervised Speech Representation for Spoken Language Modelingcited by 47
  7. 2022Towards End-to-end Unsupervised Speech Recognitioncited by 44
  8. 2021CDPAM: Contrastive learning for perceptual audio similaritycited by 42
  9. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37
  10. 2021Segmental Contrastive Predictive Coding for Unsupervised Word Segmentationcited by 32
  11. 2021Phone-to-audio alignment without text: A Semi-supervised Approachcited by 25
  12. 2022Word Segmentation on Discovered Phone Units with Dynamic Programming and Self-Supervised Scoringcited by 24
31 more
  1. 2021Acoustic word embeddings for zero-resource languages using self-supervised contrastive learning and multilingual adaptationcited by 19
  2. 2023Generative Spoken Language Model based on continuous word-sized audio tokenscited by 19
  3. 2021Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and wordscited by 18
  4. 2023The taste of IPA: Towards open-vocabulary keyword spotting and forced alignment in any languagecited by 14
  5. 2022Variable-rate hierarchical CPC leads to acoustic unit discovery in speechcited by 13
  6. 2022Phoneme Segmentation Using Self-Supervised Speech Modelscited by 11
  7. 2022A Brief Overview of Unsupervised Neural Speech Representation Learningcited by 9
  8. 2021Double Articulation Analyzer with Prosody for Unsupervised Word and Phoneme Discoverycited by 7
  9. 2021Multilingual transfer of acoustic word embeddings improves when training on languages related to the target zero-resource languagecited by 7
  10. 2023Unsupervised Word Segmentation Using Temporal Gradient Pseudo-Labelscited by 7
  11. 2023Weakly-supervised forced alignment of disfluent speech using phoneme-level modelingcited by 7
  12. 2023R-Spin: Efficient Speaker and Noise-invariant Representation Learning with Acoustic Piecescited by 7
  13. 2021Unsupervised Automatic Speech Recognition: A Reviewcited by 5
  14. 2023Unsupervised Speech Recognition with N-Skipgram and Positional Unigram Matchingcited by 5
  15. 2022Unsupervised Symbolic Music Segmentation using Ensemble Temporal Prediction Errorscited by 4
  16. 2023ParrotTTS: Text-to-Speech synthesis by exploiting self-supervised representationscited by 4
  17. 2025Exploring the Effect of Segmentation and Vocabulary Size on Speech Tokenization for Speech Language Modelscited by 4
  18. 2022Self-supervised Speaker Diarizationcited by 3
  19. 2023In-the-wild Speech Emotion Conversion Using Disentangled Self-Supervised Representations and Neural Vocoder-based Resynthesiscited by 3
  20. 2022DDKtor: Automatic Diadochokinetic Speech Analysiscited by 1
  21. 2022Learning Phone Recognition from Unpaired Audio and Phone Sequences Based on Generative Adversarial Networkcited by 1
  22. 2023Unsupervised Pre-Training For Data-Efficient Text-to-Speech On Low Resource Languagescited by 1
  23. 2023Towards Matching Phones and Speech Representationscited by 1
  24. 2024Removing Speaker Information from Speech Representation using Variable-Length Soft Poolingcited by 1
  25. 2024A Simple HMM with Self-Supervised Representations for Phone Segmentationcited by 1
  26. 2025Unsupervised Speech Segmentation: A General Approach Using Speech Language Modelscited by 1
  27. 2026Multilingual Word-Level Forced Alignment with Self-Supervised Representations and Learned Dynamic Programmingcited by 1
  28. 2026Fully Differentiable Neural Forced Alignment via Soft Dynamic Programmingcited by 1
  29. 2024Speaker- and Text-Independent Estimation of Articulatory Movements and Phoneme Alignments from Speechcited by 0
  30. 2026Phone Segmentation and Recognition through Phonological Activation Mappingcited by 0
  31. 2026Phonetic forced alignment for low-resource language varieties: Model training and evaluation on Chengdu Mandarincited by 0