mlsanityData to 14 Oct 2026

Use of Speech Impairment Severity for Dysarthric Speech Recognition

arXiv 2305.10659 ↗First posted 18 May 2023eess.AS cs.AI cs.LGcited by 8

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Abstract (arXiv)

A key challenge in dysarthric speech recognition is the speaker-level diversity attributed to both speaker-identity associated factors such as gender, and speech impairment severity. Most prior researches on addressing this issue focused on using speaker-identity only. To this end, this paper proposes a novel set of techniques to use both severity and speaker-identity in dysarthric speech recognition: a) multitask training incorporating severity prediction error; b) speaker-severity aware auxiliary feature adaptation; and c) structured LHUC transforms separately conditioned on speaker-identity and severity. Experiments conducted on UASpeech suggest incorporating additional speech impairment severity into state-of-the-art hybrid DNN, E2E Conformer and pre-trained Wav2vec 2.0 ASR systems produced statistically significant WER reductions up to 4.78% (14.03% relative). Using the best system the lowest published WER of 17.82% (51.25% on very low intelligibility) was obtained on UASpeech.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 23 of its 55 references that are in the map. First posted on arXiv 18 May 2023.

Builds on

23 of 55 references.

References · 23

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
  3. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,863
  4. 2018ESPnet: End-to-End Speech Processing Toolkitcited by 558
  5. 2016Learning Hidden Unit Contributions for Unsupervised Acoustic Model Adaptationcited by 40
  6. 2022Investigation of Data Augmentation Techniques for Disordered Speech Recognitioncited by 27
  7. 2022Speaker adaptation for Wav2vec2 based dysarthric ASRcited by 21
  8. 2022Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognitioncited by 19
  9. 2021Adversarial Data Augmentation for Disordered Speech Recognitioncited by 18
  10. 2020Improved End-to-End Dysarthric Speech Recognition via Meta-learning Based Model Re-initializationcited by 17
  11. 2022Recent Progress in the CUHK Dysarthric Speech Recognition Systemcited by 17
  12. 2022Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognitioncited by 17
11 more
  1. 2022Personalized Adversarial Data Augmentation for Dysarthric and Elderly Speech Recognitioncited by 16
  2. 2021Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasetscited by 14
  3. 2023Exploring Self-supervised Pre-trained ASR Models For Dysarthric and Elderly Speech Recognitioncited by 14
  4. 2022Spectro-Temporal Deep Features for Disordered Speech Assessment and Recognitioncited by 13
  5. 2022Neural Architecture Search For LF-MMI Trained Time Delay Neural Networkscited by 11
  6. 2022Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognitioncited by 10
  7. 2022Variational Auto-Encoder Based Variability Encoding for Dysarthric Speech Recognitioncited by 9
  8. 2022Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognitioncited by 9
  9. 2022Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognitioncited by 7
  10. 2022Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognitioncited by 7
  11. 2022Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systemscited by 4

Built on by

Cited by year (2026 to 14 Oct)

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

8 papers.

  1. 2024Self-supervised ASR Models and Features For Dysarthric and Elderly Speech Recognitioncited by 9
  2. 2024Perceiver-Prompt: Flexible Speaker Adaptation in Whisper for Chinese Disordered Speech Recognitioncited by 4
  3. 2025Adapting Foundation Speech Recognition Models to Impaired Speech: A Semantic Re-chaining Approach for Personalization of German Speechcited by 4
  4. 2024Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptationcited by 2
  5. 2025DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognitioncited by 2
  6. 2026FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognitioncited by 1
  7. 2025On-the-fly Routing for Zero-shot MoE Speaker Adaptation of Speech Foundation Models for Dysarthric Speech Recognitioncited by 0
  8. 2026Augmenting Dysarthric Speech Severity Assessment with MOS Supervisioncited by 0