mlsanityData to 7 Oct 2026

The Influence of Dataset Partitioning on Dysfluency Detection Systems

arXiv 2206.03400 ↗First posted 7 Jun 2022eess.AS cs.CL cs.SDcited by 9

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Abstract (arXiv)

This paper empirically investigates the influence of different data splits and splitting strategies on the performance of dysfluency detection systems. For this, we perform experiments using wav2vec 2.0 models with a classification head as well as support vector machines (SVM) in conjunction with the features extracted from the wav2vec 2.0 model to detect dysfluencies. We train and evaluate the systems with different non-speaker-exclusive and speaker-exclusive splits of the Stuttering Events in Podcasts (SEP-28k) dataset to shed some light on the variability of results w.r.t. to the partition method used. Furthermore, we show that the SEP-28k dataset is dominated by only a few speakers, making it difficult to evaluate. To remedy this problem, we created SEP-28k-Extended (SEP-28k-E), containing semi-automatically generated speaker and gender information for the SEP-28k corpus, and suggest different data splits, each useful for evaluating other aspects of methods for dysfluency detection.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 10 of its 23 references that are in the map. First posted on arXiv 7 Jun 2022.

Builds on

10 of 23 references.

References · 10

  1. 2017Attention Is All You Needcited by 59,932
  2. 2017Squeeze-and-Excitation Networkscited by 4,763
  3. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  4. 2019SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognitioncited by 1,355
  5. 2017VoxCeleb: a large-scale speaker identification datasetcited by 714
  6. 2020ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verificationcited by 606
  7. 2015MUSAN: A Music, Speech, and Noise Corpuscited by 400
  8. 2021Emotion Recognition from Speech Using Wav2vec 2.0 Embeddingscited by 158
  9. 2021SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stuttercited by 51
  10. 2022KSoF: The Kassel State of Fluency Dataset -- A Therapy Centered Dataset of Stutteringcited by 21

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 3; 2025: 1; 2026: 3.

9 papers.

  1. 2023A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problemcited by 9
  2. 2024FairSSD: Understanding Bias in Synthetic Speech Detectorscited by 9
  3. 2024Large Language Models for Dysfluency Detection in Stuttered Speechcited by 8
  4. 2023Whisper in Focus: Enhancing Stuttered Speech Classification with Encoder Layer Optimizationcited by 5
  5. 2025Boli: A dataset for understanding stuttering experience and analyzing stuttered speechcited by 3
  6. 2024Optimizing Multi-Stuttered Speech Classification: Leveraging Whisper's Encoder for Efficient Parameter Reduction in Automated Assessmentcited by 0
  7. 2026Multilingual Stutter Event Detection for English, German, and Mandarin Speechcited by 0
  8. 2026Virtual Speech Therapist: A Clinician-in-the-Loop AI Speech Therapy Agent for Personalized and Supervised Therapycited by 0
  9. 2026A Semi-Supervised Framework for Speech Confidence Detection using Whispercited by 0