mlsanityData to 14 Oct 2026

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

arXiv 2605.03696 ↗First posted 5 May 2026cs.CLcited by 2

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Abstract (arXiv)

The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there are various benefits to such speech-to-text systems, the choice of hyperparameters and models plays a crucial role in their performance. Typically, these choices are determined by considering only the character (CER) and/or word error rate (WER) metrics. However, it has been shown in several studies that these metrics are largely incomplete and fail to adequately describe the downstream application of automatic transcripts. In this paper, we conduct a qualitative study on the French language that investigates the impact of subword tokenization algorithms and self-supervised learning models from different linguistic and acoustic perspectives, using a comprehensive set of evaluation metrics.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 23 references that are in the map. First posted on arXiv 5 May 2026.

Builds on

14 of 23 references.

References · 14

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  3. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
  4. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  5. 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
  6. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  7. 2018Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidatescited by 639
  8. 2021XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scalecited by 601
  9. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 406
  10. 2019CamemBERT: a Tasty French Language Modelcited by 368
  11. 2021LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speechcited by 47
  12. 2021Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understandingcited by 42
2 more
  1. 2026HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metricscited by 4
  2. 2026Qualitative Evaluation of Language Model Rescoring in Automatic Speech Recognitioncited by 3

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Citing papers per year: 2026: 2.

2 papers.

  1. 2026Generative vs. Encoder Large Language Models for ASR Evaluation: A Comparative Studycited by 0
  2. 2026Rethinking Human-Aligned Evaluation: An Analysis of Semantic Metrics Beyond WERcited by 0