Dysarthric speech database for universal access research

Motor Speech Disorders

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Hmm-Based and Svm-Based Recognition of the Speech of Talkers With Spastic Dysarthria

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Bimodal speech recognition using coupled hidden Markov models

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The Alborada-I3A Corpus of Disordered Speech

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DNN acoustic models for dysarthric speech

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Improving Speech to Text Alignment Based on Repetition Detection for Dysarthric Speech

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Landmark based modification to correct distortions in dysarthric speech

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Improvement of Continuous Dysarthric Speech Quality

Prakash, A., Reddy, M. R., & Murthy, H. A. (2016) · Workshop on Speech and Language Processing for Assistive Technologies · doi:10.21437/slpat.2016-8 · Cited by 7

Acoustic cues to lexical stress in spastic dysarthria

Kim, H., Hasegawa‐Johnson, M., & Perlman, A. L. (2010) · Speech prosody · doi:10.21437/speechprosody.2010-226 · Cited by 7

Positional asymmetries in consonant production and intelligibility in dysarthric speech

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An Objective Evaluation Framework for Pathological Speech SynthesisPreprint

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Using Automatic Speech Recognition to Measure the Intelligibility of Speech Synthesized From Brain Signals

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Neural Architecture Search for LF-MMI Trained Time Delay Neural Networks

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Dysarthric Severity Categorization Based on Speech Intelligibility: A Hybrid Approach

Vidya, M., & Ganesh Vaidyanathan, S. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02770-7 · Cited by 6

Robust Cross-Etiology and Speaker-Independent Dysarthric Speech Recognition

Singh, S., Wang, Q., Zhong, Z., Mendes, C., Hasegawa‐Johnson, M., Abdulla, W. H., & Shahamiri, S. R. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10888041 · Cited by 7

An End-to-End Overview of Clinical Speech AI

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Dysarthric Speech Recognition using Depthwise Separable Convolutions: Preliminary Study

Shahamiri, S. R., Mandal, K., & Sarkar, S. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314894 · Cited by 6

Using StarGANv2 Voice Conversion to Enhance the Quality of Dysarthric Speech

Mehrez, H., Chaiani, M., & Selouani, S. (2024) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic60209.2024.10463241 · Cited by 6

Objective Estimation of Dysarthric Speech Intelligibility

Hummel, R. (2011) · Cited by 6

Assessment on impact of various types of dysarthria on acoustic parameters of speech

Giri, M. P., & Rayavarapu, N. (2018) · International Journal of Speech Technology · doi:10.1007/s10772-018-9539-0 · Cited by 6

Unsupervised Domain Adaptation for Dysarthric Speech Detection via Domain Adversarial Training and Mutual Information Minimization

Wang, D., Deng, L., Yeung, Y. T., Chen, X., Liu, X., & Meng, H. M. L. (2021) · Interspeech (USB) · doi:10.21437/interspeech.2021-2139 · Cited by 6

Analysis of Short-Time Magnitude Spectra for Improving Intelligibility Assessment of Dysarthric Speech

Sahu, L. P., & Pradhan, G. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02047-x · Cited by 6

Dysarthric Speech Recognition, Detection and Classification using Raw Phase and Magnitude Spectra

Yue, Z., Loweimi, E., & Cvetković, Z. (2023) · Interspeech (USB) · doi:10.21437/interspeech.2023-222 · Cited by 6

An Analysis of Personalized Speech Recognition System Development for the Deaf and Hard-of-Hearing

Violeta, L. P., & Toda, T. (2023) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc58517.2023.10317318 · Cited by 6

Combined approach to dysarthric speaker verification using data augmentation and feature fusion

Salim, S., Shahnawazuddin, S., & Ahmad, W. (2024) · Speech Communication · doi:10.1016/j.specom.2024.103070 · Cited by 6

Increasing the Precision of Dysarthric Speech Intelligibility and Severity Level Estimate

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A Survey on ASR Systems for Dysarthric Speech

Bharti, K., & Das, P. K. (2022) · International Conference on Artificial Intelligence and Speech Technology (AIST) · doi:10.1109/aist55798.2022.10065162 · Cited by 6

Bag of Models Based Embeddings for Assessment of Neurological Disorders Using Speech Intelligibility

Chandrakala, S., Malini, S., & Jayalakshmi, S. L. (2020) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2020.3003085 · Cited by 6

Kinematic analysis of tongue movement control in spastic dysarthria

Kim, H., Rong, P., Loucks, T. M. J., & Hasegawa‐Johnson, M. (2010) · Interspeech (USB) · doi:10.21437/interspeech.2010-697 · Cited by 6

Mapping subcortical brain lesions, behavioral and acoustic analysis for early assessment of subacute stroke patients with dysarthria

Liu, J., Ruzi, R., Jian, C., Wang, Q., Zhao, S., Ng, M. L., Zhao, S., Wang, L., & Yan, N. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1455085 · Cited by 5

Enhancing Traditional Kaldi Dysarthric Speech Recognition Using SSL-Features

Sapkota, P., Sinha, A., Kathania, H. K., & Kadiri, S. R. (2025) · National Conference on Communications · doi:10.1109/ncc63735.2025.10983605 · Cited by 5

Speaker independent dysarthria severity classification using synthesis-based augmentation

Suresh, M., Rajan, R., & Thomas, J. (2025) · International Journal of Speech Technology · doi:10.1007/s10772-025-10191-3 · Cited by 5

Detecting somatisation disorder via speech: introducing the Shenzhen Somatisation Speech Corpus

Qian, K., Huang, R., Bao, Z., Tan, Y., Zhao, Z., Sun, M., Hu, B., Schuller, B. W., & Yamamoto, Y. (2023) · Intelligent Medicine · doi:10.1016/j.imed.2023.03.001 · Cited by 6

Pretraining and Adaptation Techniques for Electrolaryngeal Speech Recognition

Violeta, L. P., Ma, D., Huang, W.-C., & Toda, T. (2024) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2024.3402557 · Cited by 6

Modeling Source and System Features Through Multi-channel Convolutional Neural Network for Improving Intelligibility Assessment of Dysarthric Speech

Ahmad, M. T., Pradhan, G., & Singh, J. P. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02739-6 · Cited by 5

Automatic detection of Parkinson's disease from components of modulators in speech signals

Sarria-Paja, M. (2020) · Computer and Electronic Sciences Theory and Applications · doi:10.17981/cesta.01.01.2020.05 · Cited by 5

Towards End-to-End Speech Articulation and Spoken Language Analysis Using Deep Learning

Weise, T., Demir, K. C., Pérez-Toro, P. A., Arias‐Vergara, T., Maier, A., Nöth, E., Schuster, M. E., Heismann, B. J., & Yang, S. H. (2025) · Human-Centric Intelligent Systems · doi:10.1007/s44230-025-00094-6 · Cited by 6

A Strategic Approach for Robust Dysarthric Speech Recognition

Revathi, A. A., Sasikaladevi, N., Arunprasanth, D., & Amirtharajan, R. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11029-y · Cited by 4

Advancing Voice Biometrics for Dysarthria Speakers Using Multitaper LFCC and Voice Conversion Data Augmentation

Salim, S., & Ahmad, W. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3484661 · Cited by 4

A Hybrid Cross-Attentive CNN-BiLSTM-Transformer Network for Dysarthria Severity Classification

Remya, M. S., Ishwar, P., & Nedungadi, P. (2025) · Scientific Reports · doi:10.1038/s41598-025-26049-2 · Cited by 5

Multimodal speech and audio user interfaces for K-12 outreach

Hasegawa‐Johnson, M., Goudeseune, C. M. A., Cole, J., Kaczmarski, H., Kim, H., King, S., Mahrt, T., Huang, J. T., Zhuang, X., Lin, K., et al. (2011) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · Cited by 4

Synthetic Speech References for Automatic Pathological Speech Intelligibility Assessment

Janbakhshi, P., Kodrasi, I., & Bourlard, H. A. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054765 · Cited by 4

Real-Time Communication Aid System for Korean Dysarthric Speech

Park, K., & Hong, J. (2025) · Applied Sciences · doi:10.3390/app15031416 · Cited by 4

Phone-purity Guided Discrete Tokens for Dysarthric Speech Recognition

Wang, H., Xie, X., Geng, M., Hu, S., Xu, H., Chen, Y., Li, Z., Deng, J., & Liu, X. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889032 · Cited by 4

Dysarthric speaker identification with constrained training durations

Chaiani, M., Bengherabi, M., Selouani, S., & Boudraa, M. (2018) · International Conference on Signal, Image, Vision and their Applications (SIVA) · doi:10.1109/siva.2018.8661100 · Cited by 4

Machine Learning Based Assistive Speech Technology for People with Neurological Disorders

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Weak Speech Supervision: A case study of Dysarthria Severity Classification

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Disentangled Latent Speech Representation for Automatic Pathological Intelligibility Assessment

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Waveform Analysis and Feature Extraction from Speech Data of Dysarthric Persons

Balaji, V., & Sadashivappa, G. (2019) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin.2019.8711768 · Cited by 4

Handling Acoustic Variation in Dysarthric Speech Recognition Systems Through Model Combination

Hermann, E., & Magimai.-Doss, M. (2021) · Interspeech (USB) · doi:10.21437/interspeech.2021-2212 · Cited by 4

On the use of array learners towards Automatic Speech Recognition for dysarthria

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A discriminative training method incorporating pronunciation variations for dysarthric automatic speech recognition

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Phase-Based Feature Representations for Improving Recognition of Dysarthric Speech

Sehgal, S., Cunningham, S. P., & Green, P. (2018) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt.2018.8639031 · Cited by 4

A Spanish multispeaker database of esophageal speech

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The Open-Access Mandarin Subacute Stroke Dysarthria Multimodal (MSDM) Database for Intelligent Assessment

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A Multi-modal Approach to Dysarthria Detection and Severity Assessment Using Speech and Text Information

Anuprabha, M., Gurugubelli, K., Kesavaraj, V., & Vuppala, A. K. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889515 · Cited by 5

Convolution-Augmented Transformers for Enhanced Speaker-Independent Dysarthric Speech Recognition

Zhong, Z., Wang, Q., Singh, S., Mendes, C., Hasegawa‐Johnson, M., Abdulla, W. H., & Shahamiri, S. R. (2025) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2025.3610792 · Cited by 5

Speech Recognition for Individuals with Voice Disorders

Moore, M. (2021) · Springer eBooks · doi:10.1007/978-3-030-70716-3_5 · Cited by 3

Comparative landmark detection on stops of dysarthric speech

Sunitha, S. V., Putra, S., & Soundeswaran, S. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.104125 · Cited by 3

Re-Talk: Automated Speech Assistance for People with Dysarthria

Ali, S. K., Hassan, A. M., Salah, A. M., Mohamed, D. W., Mustafa, M., & Mohamed, E. H. (2023) · النشرة المعلوماتية في الحاسبات والمعلومات · doi:10.21608/fcihib.2023.188592.1077 · Cited by 3

PB-LRDWWS System For the SLT 2024 Low-Resource Dysarthria Wake-Up Word Spotting Challenge

Wang, S., Zhou, J., Zhao, S., & Qin, Y. (2024) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt61566.2024.10832235 · Cited by 3

A Study on Model Training Strategies for Speaker-Independent and Vocabulary-Mismatched Dysarthric Speech Recognition

Qi, J., & hamme, H. V. (2025) · Applied Sciences · doi:10.3390/app15042006 · Cited by 3

Improving Generalisation to New Speakers in Spoken Dialogue State Tracking

Casanueva, I., Hain, T., & Green, P. (2016) · Interspeech (USB) · doi:10.21437/interspeech.2016-404 · Cited by 3

Intelligibility assessment of impaired speech using Regularized self-representation based compact supervectors

Malini, S., & Chandrakala, S. (2022) · Computer Speech & Language · doi:10.1016/j.csl.2022.101355 · Cited by 3

Denoising Convolutional Autoencoder Based Approach for Disordered Speech Recognition

Chandrakala, S., & Veni, S. V. (2023) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213023500586 · Cited by 2

Dysarthric Speech Recognition: A Comparative Study

Shah, D. K., Lal, V., Zhong, Z., Wang, Q., & Shahamiri, S. R. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314881 · Cited by 2

DySARNet: a lightweight self-attention deep learning model for diagnosing dysarthria from speech recordings

Montalbo, F. J. P. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20053-w · Cited by 2

Analysis and development of clinically recorded dysarthric speech corpus for patients affected with various stroke conditions

Banerjee, O., Mahalakshmi, K. V. N. S., Jyothi, M. V. S., Govind, D., Rakesh, U. K., Rajeev, A., Samudravijaya, K., Dubey, A. K., & Gangashetty, S. V. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100198 · Cited by 4

Long-Range and Non-Stationary Encoding for Dysarthric Speech Data Augmentation

Zhang, D. W., Zhang, H., Lu, W., Li, W., Wang, J., & Wei, J. (2025) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2025.3562417 · Cited by 2

Gestural feature extraction and multi-feature co-activation for dysarthric speech recognition

Lin, Y., Wang, L., Dang, J., & Minematsu, N. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103490 · Cited by 2

Hierarchical Curriculum Learning for Dysarthric Speech Recognition via Multi-Level Knowledge Distillation

Hsieh, I.-T., & Wu, C. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3597438 · Cited by 2

Categorization of patients affected with neurogenerative dysarthria among Hindi-speaking population and analyzing factors causing reduced speech intelligibility at the human-machine interface

Kumar, R., Tripathy, M., Kumar, N., & Anand, R. S. (2025) · Speech Communication · doi:10.1016/j.specom.2025.103328 · Cited by 2

Dysarthric Speech Classification: A Comparative Analysis of Decision-Support Methods

Lillini, D., Aironi, C., Migliorelli, L., Gabrielli, L., & Squartini, S. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11228715 · Cited by 2

Improved Dysarthric Speech to Text Conversion via TTS Personalization

Mihajlik, P., Székely, É., Barta, P. Z., Kádár, M. S., Dobsinszki, G., & Tóth, L. (2025) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco63237.2025.11226704 · Cited by 2

Vowel Formant Transformation Techniques for Dysarthric Speech

Varghese, A., Sowmya, M., & Karjigi, V. (2019) · International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT) · doi:10.1109/iceeccot46775.2019.9114558 · Cited by 2

Development of CNN-based robust dysarthric isolated digit recognition system by enhancing speech intelligibility

Revathi, A. A., Sasikaladevi, N., & Arunprasanth, D. (2022) · Research on Biomedical Engineering · doi:10.1007/s42600-022-00239-7 · Cited by 2

Modeling Sub-Band Information Through Discrete Wavelet Transform to Improve Intelligibility Assessment of Dysarthric Speech.

Sahu, L. P., Pradhan, G., & Singh, J. P. (2022) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2022.10.003 · Cited by 2

Analysis and Classification Dysarthric Speech

Gupta, S., & Patil, H. A. (2022) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-15816-2_9 · Cited by 2

Suppressing Noise Disparity in Training data for Automatic Pathological Speech Detection

Amiri, M., & Kodrasi, I. (2024) · International Workshop on Acoustic Signal Enhancement · doi:10.1109/iwaenc61483.2024.10694597 · Cited by 2

Check Your Audio Data: Nkululeko for Bias Detection

Burkhardt, F., Atmaja, B. T., Derington, A., Eyben, F., & Schuller, B. W. (2024) · International Conference on Speech Database and Assessments · doi:10.1109/o-cocosda64382.2024.10800580 · Cited by 3

Dysarthria Severity Classification Using Phase Based Features of LP Residual

Mannepalli, R. S., Pusuluri, A., & Patil, H. A. (2024) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc63619.2025.10848959 · Cited by 2

Homogeneous Speaker Features for on-the-Fly Dysarthric and Elderly Speaker Adaptation and Speech Recognition

Geng, M., Xie, X., Deng, J., Jin, Z., Li, G., Wang, T., Hu, S., Li, Z., Meng, H. M. L., & Liu, X. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3547217 · Cited by 5

A Comprehensive Performance Evaluation of Whisper Models in Dysarthric Speech Recognition

Singh, S., Zhong, Z., Wang, Q., Mendes, C., Hasegawa‐Johnson, M., Abdulla, W. H., & Shahamiri, S. R. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-6960-8_6 · Cited by 3

Resolving Domain Mismatches in Electrolaryngeal Speech Enhancement With Linguistic Intermediates

Violeta, L. P., Huang, W.-C., Ma, D., Yamamoto, R., Kobayashi, K., & Toda, T. (2025) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2025.3584195 · Cited by 2

Abnormal Speech Restoration for Speech Impaired Patients Using Deep Learning: Literature Survey

Mohammed, O. A., & Al-Shakarchy, N. D. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-00712-4_20 · Cited by 2

Contemporary speech/speaker recognition with speech from impaired vocal apparatus

Nidhyananthan, S. S., Kumari, R. S. S., & Shenbagalakshmi, V. (2014) · International Conference on Communication and Network Technologies (ICCNT) · doi:10.1109/cnt.2014.7062754 · Cited by 2

Isolated Word Recognition using Neural Network for Disordered Speech

Chadha, A. N., Zaveri, M. A., & Sarvaiya, J. N. (2016) · IASTED International Conference on Telehealth and Assistive Technology (TAT) · doi:10.2316/p.2016.846-005 · Cited by 2

Real time detection of fricative landmarks to modify distortion in dysarthric speech using TMS320C6713 DSK

Sultana, S., S, P. K., Karjigi, V., & Rao, D. M. (2016) · Conference on Advances in Signal Processing (CASP) · doi:10.1109/casp.2016.7746173 · Cited by 2

Using phone features to improve dialogue state tracking generalisation to unseen states

Casanueva, I., Hain, T., Nicolao, M., & Green, P. (2016) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/w16-3611 · Cited by 2

MLLR Based Speaker Adaptation for Indian Accents

Balaji, A. G. S., V (2017) · International Journal of Computing and Digital Systems · doi:10.12785/ijcds/060508 · Cited by 2

Parkinson’s disease detection using modulation components in speech signals

Moofarry, J. F., Sarria-Paja, M., & Orozco‐Arroyave, J. R. (2019) · Symposium on Image, Signal Processing and Artificial Vision (STSIVA) · doi:10.1109/stsiva.2019.8730245 · Cited by 2

Domain Adversarial Neural Networks for Dysarthric Speech Recognition

Woszczyk, D. C., Petridis, S., & Millard, D. E. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2845 · Cited by 2

Automatic Speech Intelligibility Assessment in Dysarthric Subjects

Tripathi, A., Bhosale, S., & Kopparapu, S. K. (2020) · International Conference on the Digital Society · Cited by 2

Determining the adaptation data saturation of ASR systems for dysarthric speakers

Al-Qatab, B. A., Mustafa, M. B., Salim, S. S., & Sani, A. A. (2021) · International Journal of Speech Technology · doi:10.1007/s10772-020-09788-7 · Cited by 2

Improving the intelligibility of dysarthric speech using a time domain pitch synchronous-based approach

Giri, M. P., & Rayavarapu, N. (2023) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v13i4.pp4041-4051 · Cited by 2

Cochlear Filter-Based Cepstral Features for Dysarthric Severity-Level Classification

Rathod, S., Gupta, P., Kachhi, A., & Patil, H. A. (2023) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco58844.2023.10289888 · Cited by 2

Pathological voice adaptation with autoencoder-based voice conversion

Illa, M., Halpern, B. M., van Son, R. J. J. H., Moro-Velázquez, L., & Scharenborg, O. (2021) · ISCA Speech Synthesis Workshop (SSW) · doi:10.21437/ssw.2021-4 · Cited by 2

Introduction

Baghai-Ravary, L., & Beet, S. W. (2012) · Springer briefs in electrical and computer engineering · doi:10.1007/978-1-4614-4574-6_1 · Cited by 2

Speech-enabled environmental control in an AAL setting for people with speech disorders: a case study

Christensen, H., Nicolao, M., Cunningham, S. P., Green, P., Deena, S., & Hain, T. (2015) · IET International Conference on Technologies for Active and Assisted Living (TechAAL) · doi:10.1049/ic.2015.0129 · Cited by 2

Adversarial Data Augmentation for Disordered Speech RecognitionPreprint

Jin, Z., Geng, M., Xie, X., Yu, J., Liu, S., Liu, X., & Meng, H. M. L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.00899 · Cited by 2

Recent Advances in Dysarthric Speech Recognition: Approaches and Datasets

Alrajhi, T., Ykhlef, M., & Alsanad, A. (2024) · Journal of King Abdulaziz University-Computing and Information Technology Sciences · doi:10.4197/comp.13-2.3 · Cited by 1

Dysarthric Speech Data Augmentation Using Generative Adversarial Networks

Yadav, S., & Yadav, D. M. (2025) · International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) · doi:10.1109/icaect63952.2025.10958874 · Cited by 1

A Dutch Dysarthric Speech Database for Individualized Speech Therapy Research

Yılmaz, E., Ganzeboom, M., Beijer, L. J., Catia Cucchiarini, A., & Strik, H. (2016) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/43k9ua43iijn · Cited by 15

The TORGO database of acoustic and articulatory speech from speakers with dysarthria

Rudzicz, F., Namasivayam, A. K., & Wolff, T. (2012) · Language Resources and Evaluation · doi:10.1007/s10579-011-9145-0 · Cited by 425

The Whitaker database of dysarthric (cerebral palsy) speech

Deller, J. R., Liu, M. S., Ferrier, L. J., & Robichaud, P. H. (1993) · The Journal of the Acoustical Society of America · doi:10.1121/1.405684 · Cited by 32

Towards a comparative database . . .

Rudzicz, F., Lieshout, P. H. H. M. V., Hirst, G., Penn, G., Shein, F., & Wolff, T. (2008)

Dysarthric Speech Database for Development of QoLT Software Technology

Choi, D.-L., Kim, B., Kim, Y.-W., Lee, Y., Um, Y., & Chung, M. (2012) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/56sr2r8k36ya · Cited by 10