Unsupervised Cross-Lingual Representation Learning for Speech Recognition

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805 · Cited by 73,173

Momentum Contrast for Unsupervised Visual Representation LearningPreprint

He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. B. (2019) · Computer Vision and Pattern Recognition · doi:10.48550/arxiv.1911.05722 · Cited by 16,250

Momentum Contrast for Unsupervised Visual Representation Learning

He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00975 · Cited by 13,347

Deep Contextualized Word Representations

Peters, M., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., & Zettlemoyer, L. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) · doi:10.18653/v1/n18-1202 · Cited by 11,983

A simple framework for contrastive learning of visual representations

Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020) · arXiv · doi:10.48550/arxiv.2002.05709 · Cited by 10,857

Representation Learning with Contrastive Predictive Coding

Oord, A. V. D., Li, Y., & Vinyals, O. (2018) · arXiv · doi:10.48550/arxiv.1807.03748 · Cited by 6,242

Unsupervised Cross-lingual Representation Learning at Scale

Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.747 · Cited by 5,637

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks

Graves, A., Fernández, S., Gomez, F., & Schmidhuber, J. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143891 · Cited by 5,370

Language Bias in Self-Supervised Learning For Automatic Speech Recognition

Storey, E., Harte, N., & Bell, P. (2024) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt61566.2024.10832268 · Cited by 2

Cohort-Sensitive Labeling: An Effective Approach for Enhancing ASR Performance

Na, J., Hasegawa‐Johnson, M., & Lee, B. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890600 · Cited by 1

Speech Separation for Low-Resource Languages

Borsdorf, M., Pan, Z., Himmelmann, P., Li, H., & Schultz, T. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10888872 · Cited by 1

CASC-XVC: Zero-Shot Cross-Lingual Voice Conversion with Content Accordant and Speaker Contrastive Losses

Guo, H.-J., Du, H.-P., Sheng, Z.-Y., Chen, L., Ai, Y., & Ling, Z.-H. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889831 · Cited by 1

DQ-Data2vec: Decoupling Quantization for Multilingual Speech Recognition

Shao, Q., Dong, L., Wei, K., Sun, S., & Xie, L. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3551074 · Cited by 1

Formant-based vowel categorization for cross-lingual phone recognition

Stepanović, M., Hardmeier, C., & Scharenborg, O. (2025) · The Journal of the Acoustical Society of America · doi:10.1121/10.0036222 · Cited by 1

A low-channel EEG-to-speech conversion approach for assisting people with communication disorders

Shen, K., & Li, H. (2025) · Smart Health · doi:10.1016/j.smhl.2025.100568 · Cited by 1

Use of Pre-Trained Multilingual Models for Karelian Speech Recognition

Kipyatkova, I. S., Kagirov, I., & Dolgushin, M. (2025) · Informatics and Automation · doi:10.15622/ia.24.2.9 · Cited by 1

Minerva 2 for speech and language tasks

Mogridge, R., & Ragni, A. (2025) · Computer Speech & Language · doi:10.1016/j.csl.2025.101843 · Cited by 1

Early Detection of ALS in Absence of Speech Impairments with Computer Audition

Mallol-Ragolta, A., Gonzalez-Machorro, M., von Heynitz, R. K., Scherzer, K. Y., Cordts, I., & Schuller, B. W. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-95838-0_27 · Cited by 1

HealthBridge: A Cross-lingual Clustering Framework for English-Chinese Health News

Zuo, C., Wang, C., & Wu, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-0020-8_36 · Cited by 1

Multilingual Translation for Speech and Text using Whisper AI: A Deep Learning Approach

Saraf, A. (2025) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2025.73288 · Cited by 1

Segmentation-Free Goodness of Pronunciation

Cao, X., Fan, Z., Svendsen, T. K., & Salvi, G. (2026) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2026.3654852 · Cited by 1

Enhancement of Dysarthric Speech Reconstruction by Contrastive Learning

Keshvari, F., Toroghi, R. M., & Zareian, H. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-90893-4_51 · Cited by 1

TamilFacts: A Comprehensive Multimodal Dataset of Fact-Checked Social Media Content in Tamil Language

Francis, M. A., Kurup, A. R., Premjith, B., Chakravarthi, B. R., & Saranya, R. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-05855-3_13 · Cited by 1

Advancing End-To-End Indonesian Speech Emotion Recognition Using XLSR-Wav2Vec2

Nugroho, K. S., Iriananda, S. W., Akbar, I., Isnan, M., & Pardamean, B. (2025) · International Conference on Information Technology Research and Innovation (ICITRI) · doi:10.1109/icitri67507.2025.11232655 · Cited by 1

Accent-robust speech recognition for English in low-resource settings using Manifold Mixup

Banerjee, T., & Ramasubramanian, V. (2025) · EURASIP Journal on Audio Speech and Music Processing · doi:10.1186/s13636-025-00435-0 · Cited by 1

Prediction of self-reported and external observations of conversational engagement in online group discussions

Russell, S. O., Reverdy, J., Cowan, B., & Harte, N. (2025) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-025-00471-2 · Cited by 1

Modeling Intra-word Code-Switching for Karelian ASR

Kipyatkova, I. S., Kiseleva, K., Dolgushin, M., & Kagirov, I. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-07959-6_8 · Cited by 1

Enhancing Low-Resource Speech Recognition With Non-Linear Cross-Lingual Mappings

Farooq, M. U., & Hain, T. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3626241 · Cited by 1

Whisper Based Cross-Lingual Phoneme Recognition Between Vietnamese and English

Nguyen, H. N. M., Tran, N. A., Truong, D. D., Vo, V. N., & Le, P. T. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-00972-2_20 · Cited by 1

Transformer-Based Neural Network Approaches for Speech Recognition and Synthesis in the Sakha Language

Stepanov, S. P., Zhang, D., Alekseeva, A. A., Aprosimov, V. L., Fedorov, D. A., Leveryev, V. S., Novgorodov, T. A., Podorozhnaya, E. S., & Zakharov, T. Z. (2026) · Arctic XXI century · doi:10.25587/3034-7378-2025-4-56-78 · Cited by 1

When Data Is Scarce: Training a Kazakh Speech Language Model from Discrete Units

Kairatuly, B., & Mansurova, M. (2026) · Applied Sciences · doi:10.3390/app16041773 · Cited by 1

Splat-Portrait: Generalizing Talking Heads with Gaussian Splatting

Shi, T., de Almeida, M., Ivanova, D., Pugeault, N., & Henderson, P. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-6950-2_35 · Cited by 1

Multilingual speech representation for the Manipuri automatic speech recognition system

Devi, T. C., Thaoroijam, K., & Nongmeikapam, K. (2026) · Language Resources and Evaluation · doi:10.1007/s10579-026-09908-w · Cited by 1

Layer-wise Analysis for Quality of Multilingual Synthesized Speech

Cooper, E., Okamoto, T., Ohtani, Y., Toda, T., & Kawai, H. (2025) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru65441.2025.11434769 · Cited by 1

FAC-FACodec: Controllable Zero-Shot Foreign Accent Conversion with Factorized Speech Codec

Halychanskyi, Y., Churchwell, C., Wen, Y., & Kindratenko, V. (2026) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp55912.2026.11461516 · Cited by 1

Enhancing multilingual automatic speech recognition for low-resource code-switched languages: a scalable data augmentation strategy

Morsi, M. M., Fathalla, R., Abdou, S. M., & Fakhr, M. W. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3877 · Cited by 1

From Speech to Summary in Turkmen: A Parameter-Efficient Neural Pipeline

Tukeyev, U., & Ocheretin, M. (2026) · Applied Sciences · doi:10.3390/app16125734 · Cited by 1

Mental Wellbeing at Sea: Active and Passive Speech Monitoring in a Maritime Setting

Hecker, P., Gonzalez-Machorro, M., Sagha, H., Dudeja, S., Kahlau, M., Derington, A., Eyben, F., Schuller, B. W., & Arnrich, B. (2026) · SN Computer Science · doi:10.1007/s42979-026-05107-0 · Cited by 1

“Does it Matter When I Think You Are Lying?” Improving Deception Detection by Integrating Interlocutor’s Judgements in Conversations

Chou, H.-C., Chien, W.-S., Juan, D.-C., & Lee, C.-C. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.162 · Cited by 1

A Study on the improvement of chinese automatic speech recognition accuracy using a lexicon

Gu, M.-J., & Kang, S. (2022) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic54071.2022.9722645 · Cited by 1

Non-Parametric Bayesian Subspace Models for Acoustic Unit Discovery

Ondel, L., Yusuf, B., Burget, L., & Saraçlar, M. (2022) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2022.3171975 · Cited by 1

Modèles neuronaux pré-appris par auto-supervision sur des enregistrements de parole en français

Evain, S. V., Nguyen, H., Le, H., Boito, M. Z., Mdhaffar, S., Alisamir, S., Tong, Z., Tomashenko, N., Dinarelli, M., Parcollet, T., et al. (2022) · Journées d'Études sur la Parole (JEP) · doi:10.21437/jep.2022-45 · Cited by 2

Phoneme transcription of endangered languages: an evaluation of recent ASR architectures in the single speaker scenario

Boulianne, G. (2022) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2022.findings-acl.180 · Cited by 2

Urgency Status Classification of Multilingual Medical Emergency Tweets Using Transformer-based Cross-Lingual Encoders

Singh, M., Agarwal, K., Verma, K., & Yadav, R. K. (2022) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite53722.2022.9823667 · Cited by 1

From Start to Finish: Latency Reduction Strategies for Incremental Speech Synthesis in Simultaneous Speech-to-Speech Translation

Liu, D., Wang, C., Gong, H., Ma, X., Tang, Y., & Pino, J. (2022) · Interspeech (USB) · doi:10.21437/interspeech.2022-10568 · Cited by 1

Using Self-learning Representations for Objective Assessment of Patient Voice in Dysphonia

Dang, S., Matsumoto, T., Takeuchi, Y., Kudo, H., Tsuboi, T., Tanaka, Y. R., & Katsuno, M. (2022) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.23919/apsipaasc55919.2022.9980071 · Cited by 1

Data Analytics and Aggregation Platform for Comprehensive City-Scale AI Modeling

Sornlertlamvanich, V., Iamtrakul, P., Horanont, T., Hnoohom, N., Wongpatikaseree, K., Yuenyong, S., Angkapanichkit, J., Piyapasuntra, S., Lopkerd, P., Prasertsuk, S., et al. (2023) · Frontiers in artificial intelligence and applications · doi:10.3233/faia220495 · Cited by 1

Multilingual Zero Resource Speech Recognition Base on Self-Supervise Pre-Trained Acoustic Models

Wang, H., Zhang, W.-Q., Suo, H., & Wan, Y. (2022) · International Symposium on Chinese Spoken Language Processing (ISCSLP) · doi:10.1109/iscslp57327.2022.10037938 · Cited by 1

Improving Luxembourgish Speech Recognition with Cross-Lingual Speech Representations

Nguyen, L.-M., Nayak, S., & Coler, M. (2023) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt54892.2023.10022706 · Cited by 1

English-Filipino Speech Topic Tagger Using Automatic Speech Recognition Modeling and Topic Modeling

Tumpalan, J. K. B., & Recario, R. N. C. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-28073-3_31 · Cited by 1

An Approach for Identification of Speaker using Deep Learning

Rabia, S., Haider, S. M., & Basit, A. (2023) · International Journal of Artificial Intelligence & Mathematical Sciences · doi:10.58921/ijaims.v1i2.36 · Cited by 1

Analyzing Gender Detection in Speech in Adult Filipino Citizens

Abella, M. G. J., Borja, J. M. L., Zuñiga, A. C. F., & Goma, J. C. D. (2022) · International Conference on Software Technology and Engineering · doi:10.1109/icste57415.2022.00018 · Cited by 1

A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition

Li, J., Wu, X., Song, K., Li, D., Liu, X., & Meng, H. M. L. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096395 · Cited by 1

Adaptation of a multilingual speech representation model for a new, underresourced language via multilingual fine-tuning and continued pretraining

Nowakowski, K., Ptaszynski, M. E., Murasaki, K., & Nieuważny, J. (2023) · Science Talks · doi:10.1016/j.sctalk.2023.100249 · Cited by 1

Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition

Kataria, S., Villalba, J., Moro-Velázquez, L., Thebaud, T., & Dehak, N. (2023) · Interspeech (USB) · doi:10.21437/interspeech.2023-2031 · Cited by 1

On the Nature of Discrete Speech Representations in Multilingual Self-supervised Models

Abdullah, B. M., Shaik, M. M., & Klakow, D. (2023) · Workshop on Research in Computational Linguistic Typology and Multilingual NLP (SIGTYP) · doi:10.18653/v1/2023.sigtyp-1.20 · Cited by 1

Combining Multi-scale and Self-Supervised Features for Speech Emotion Recognition

Lei, F., Wang, Z., & Ding, Y. (2023) · Chinese Control Conference (CCC) · doi:10.23919/ccc58697.2023.10239882 · Cited by 1

Bilingual ASR model with language identification for Brazilian Portuguese and South-American Spanish

Farias, F., Castañeda, W. A. C., Lobato, W., & Amadeus, M. (2023) · Anais de XXXV Simpósio Brasileiro de Telecomunicações e Processamento de Sinais · doi:10.14209/sbrt.2023.1570916069 · Cited by 1

Analysis of a Hinglish ASR System’s Performance for Fraud Detection

Rangappa, P., Brahma, A. K., Vayyavuru, V., Yadav, R., Misra, H., & Karuna, K. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48312-7_4 · Cited by 1

Finetuning Pretrained Model with Embedding of Domain and Language Information for ASR of Very Low-Resource Settings

Soky, K., Li, S., Chu, C., & Kawahara, T. (2023) · International Journal of Asian Language Processing · doi:10.1142/s2717554523500248 · Cited by 1

XLS-R fine-tuning on noisy word boundaries for unsupervised speech segmentation into words

Algayres, R., Diego-Simón, P., Sagot, B., & Emmanuel Dupoux, A. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.810 · Cited by 3

UrduSpeakXLSR: Multilingual Model for Urdu Speech Recognition

Mohiuddin, H., Ahmed, Z., Kasi, M., & Kasi, B. K. (2023) · International Conference on Emerging Technologies · doi:10.1109/icet59753.2023.10374900 · Cited by 1

Optimizing Two-Pass Cross-Lingual Transfer Learning: Phoneme Recognition And Phoneme To Grapheme Translation

Lee, W., Lee, G. G., & Kim, Y. (2023) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru57964.2023.10389737 · Cited by 1

Detection of Vowel Errors in Children’s Speech using Synthetic Phonetic Transcripts

Baumann, I., Wagner, D., Riedhammer, K., Nöth, E., & Bocklet, T. (2023) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru57964.2023.10389704 · Cited by 1

Parameter-Efficient Tuning with Adaptive Bottlenecks for Automatic Speech Recognition

Vanderreydt, G., Prasad, A., Khalil, D., Madikeri, S. R., Demuynck, K., & Motlíček, P. (2023) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru57964.2023.10389769 · Cited by 2

Comparative Assessment of Embedded Devices for Natural Language Processing for Biomedical Applications in Spanish

Jonathan, Z. D., Olivares-Rojas, J. C., Gnecchi, J. A. G., Téllez-Anguiano, A. D. C., Alcaraz-Chavez, J. E., & Reyes‐Archundia, E. (2023) · IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) · doi:10.1109/ropec58757.2023.10409471 · Cited by 1

Distilling Distributional Uncertainty from a Gaussian Process

Wong, J. H. M., & Chen, N. F. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10448172 · Cited by 1

M2BART: Multilingual and Multimodal Encoder-Decoder Pre-Training for Any-to-Any Machine Translation

Chen, P., Shi, B., Niu, K., Lee, A., & Hsu, W.-N. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446620 · Cited by 1

Advances in Cantonese Speech Recognition: A Language-Specific Pretraining Model and RNN-T Loss

Guan, J., Xu, M., Xuan, X., Fang, L., Chen, Y., & He, L. (2023) · International Academic Exchange Conference on Science and Technology Innovation (IAECST) · doi:10.1109/iaecst60924.2023.10503177 · Cited by 1

Leveraging Wav2Vec2.0 for Kazakh Speech Recognition: An Experimental Study

Kozhirbayev, Z. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64608-9_8 · Cited by 1

Automatic Speech Recognition and Assessment Systems Incorporated into Digital Therapeutics for Children with Autism Spectrum Disorder

Lee, S., Mun, J., Kim, S., Park, H.-J., Yang, S., Kim, H., Noh, S., Kim, W., & Chung, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-62849-8_40 · Cited by 1

Bridging the Gap: Developing an Automatic Speech Recognition System for Egyptian Dialect Integration Into Chatbots

Nabil, M., Abdalla, A., Sharaf, N., & Sabty, C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-70242-6_12 · Cited by 1

Enhancing spoken term detection with deep acoustic word embeddings and cross-modal matching techniques

Chantangphol, P., Sakdejayont, T., & Chalothorn, T. (2024) · International Journal of Speech Technology · doi:10.1007/s10772-024-10145-1 · Cited by 1

Emotion Manipulation Through Music - A Deep Learning Interactive Visual Approach

Abdalla, A. N., Osborne, J., & Andonie, R. (2024) · International Conference on Information Visualisation (IV) · doi:10.1109/iv64223.2024.00044 · Cited by 1

Transfer Learning of Large Speech Models for Italian Speech Emotion Recognition

D’Asaro, F., Villacís, J. J. M., & Rizzo, G. F. (2024) · IEEE International Conference on Application of Information and Communication Technologies (AICT) · doi:10.1109/aict61888.2024.10740425 · Cited by 1

A Parameter-Efficient Multi-Step Fine-Tuning of Multilingual and Multi-Task Learning Model for Japanese Dialect Speech Recognition

Kamiya, Y., Miwa, S., & Kai, A. (2024) · International Conference on Speech Database and Assessments · doi:10.1109/o-cocosda64382.2024.10800608 · Cited by 1

An Investigation of Reprogramming for Cross-Language Adaptation in Speaker Verification Systems

Li, J., Chiu, A. Y. F., & Lee, T. (2024) · International Symposium on Chinese Spoken Language Processing (ISCSLP) · doi:10.1109/iscslp63861.2024.10800573 · Cited by 1

Continual Learning With Embedding Layer Surgery and Task-Wise Beam Search Using Whisper

Kwok, C. Y., Yip, J. Q., & Chng, E. S. (2024) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt61566.2024.10832213 · Cited by 1

Improved Recognition of the Speech of People with Parkinson’s Who Stutter

Na, J., Zheng, X., Lee, B., & Hasegawa‐Johnson, M. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889229 · Cited by 1

Utilizing Neural Transducers for Two-Stage Text-to-Speech via Semantic Token Prediction

Kim, M., Jeong, M., Choi, B. J., Kim, S., Lee, J. Y., & Kim, N. S. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3566247 · Cited by 1

Vector Field Decomposition-Based Flow Matching for Zero-Shot Cross-Lingual Text-to-Speech

Lee, J., Song, N.-S., & Chang, J. (2025) · IEEE Signal Processing Letters · doi:10.1109/lsp.2025.3571407 · Cited by 1

Evaluation of German Automatic Speech Recognition solutions in the context of speech and language therapy support of people with aphasia

Rykova, E., & Walther, M. (2025) · Loquens · doi:10.3989/loquens.2025.e116 · Cited by 1

Three Years of VoiceMOS Challenges: Lessons Learned by the UWB-NTIS-TTS Team

Kunešová, M., Matoušek, J., Lehečka, J., Švec, J., Tihelka, D., & Hanzlíček, Z. (2025) · IEEE Access · doi:10.1109/access.2025.3596644 · Cited by 2

Exploring the Impact of Data Quantity on Asr in Extremely Low-Resource Languages

Cheng, Y.-F., Chen, L.-W., Lee, H.-S., & Wang, H. L. (2025) · International Conference on Speech Database and Assessments · doi:10.1109/o-cocosda68185.2025.11385096 · Cited by 2

SMILE: Speech Meta In-Context Learning for Low-Resource Language Automatic Speech Recognition

Hsu, M.-H., & Lee, H.-Y. (2025) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru65441.2025.11434760 · Cited by 14

A Restriction Training Recipe for Speech Separation on Sparsely Mixed Speech

Dang, S., Matsumoto, T., Kudo, H., & Takeuchi, Y. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-92310-5_85 · Cited by 1

Evaluating Novel Speech Transcription Architectures on the Spanish RTVE2020 Database

Álvarez, A., Arzelus, H., Torre, I. G., & González-Docasal, A. (2022) · Applied Sciences · doi:10.3390/app12041889 · Cited by 2

Cross-Lingual Transfer for Speech Processing Using Acoustic Language Similarity

Wu, P., Shi, J., Zhong, Y., Watanabe, S., & Black, A. W. (2021) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru51503.2021.9688276 · Cited by 1

Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptation

López, F., & Luque, J. (2022) · IberSPEECH · doi:10.21437/iberspeech.2022-10 · Cited by 2

CRIM’s Speech Recognition System for OpenASR21 Evaluation with Conformer and Voice Activity Detector Embeddings

Gupta, V., & Boulianne, G. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20980-2_21 · Cited by 1

M2ASR-KIRGHIZ: A Free Kirghiz Speech Database and Accompanied Baselines

Mamtimin, I., Du, W., & Hamdulla, A. (2023) · Information · doi:10.3390/info14010055 · Cited by 1

Proposing XLSR Multilingual Model for Vietnamese Language Recognition

Huu, P. N., Sy, T. H., Bao, C. N. L., Anh, M. N., Thien, L. N., Đức, H. N., Pham, M.-T., Tien, D. V., & Minh, Q. T. (2022) · RIVF International Conference on Computing and Communication Technologies (RIVF) · doi:10.1109/rivf55975.2022.10013877 · Cited by 1

Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences

Tseng, Y., Lai, C.-I., & Lee, H.-Y. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10094575 · Cited by 1

I2R’s End-to-End Speech Translation System for IWSLT 2023 Offline Shared Task

Huzaifah, M., Tan, K. M., & Duan, R. (2023) · International Conference on Spoken Language Translation (IWSLT) · doi:10.18653/v1/2023.iwslt-1.16 · Cited by 1

Ensuring the Inclusive Use of Natural Language Processing in the Global Response to COVID-19Preprint

Luccioni, A. S., Pham, K. H., Lam, C. S. N., Aylett-Bullock, J., & Luengo-Oroz, M. A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.10791 · Cited by 1

Speech Emotion Recognition in Italian Using Wav2Vec 2.0 and the Novel Crowdsourced Emotional Speech Corpus EmozionalmentePreprint

Catania, F. (2023) · doi:10.36227/techrxiv.22821992 · Cited by 1

Enhancing spoken language identification and diarization for multilingual speech

Liu, H. (2023) · doi:10.32657/10356/168498 · Cited by 1

Informed Speech Self-supervised Representation Learning

Zaiem, S. (2024) · theses.fr (ABES) · doi:10.70675/dc53ad72z177fz4bb4z91fbzd00576ba3f2e · Cited by 1

Any-to-One Sequence-to-Sequence Voice Conversion using Self-Supervised Discrete Speech RepresentationsPreprint

Huang, W.-C., Wu, Y.-C., Hayashi, T., & Toda, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.12231

Fusing Wav2vec2.0 and BERT into End-to-end Model for Low-resource Speech RecognitionPreprint

Cheng, Y., Zhou, S., & Xu, B. (2021) · arXiv (Cornell University)

Let Your Heart Speak in its Mother Tongue: Multilingual Captioning of Cardiac SignalsPreprint

Kiyasseh, D., Zhu, T., & Clifton, D. A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.11011 · Cited by 1

Topic Model Robustness to Automatic Speech Recognition Errors in Podcast TranscriptsPreprint

Fetic, R. A., Jordahn, M., Lima, L. C., Egebæk, R. A. F., Nielsen, M. C., Biering, B., & Hansen, L. K. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.12306

Cascaded Multilingual Audio-Visual Learning from VideosPreprint

Rouditchenko, A., Boggust, A., Harwath, D. F., Thomas, S., Kuehne, H., Chen, B., Panda, R., Feris, R., Kingsbury, B. E. D., Picheny, M., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.04823

Overview

YAGAWA, G., & Oishi, A. (2022) · Lecture notes on numerical methods in engineering and sciences · doi:10.1007/978-3-031-11847-0_1

The TNT Team System Descriptions of Cantonese, Mongolian and Kazakh for IARPA OpenASR21 Challenge

Tang, K., Zhao, J., Yan, J., Kang, J., Wang, H., Li, J., Chai, S., Wang, G.-B., Huang, S., Chen, G., et al. (2022) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.23919/apsipaasc55919.2022.9979820

Les modèles pré-entraînés à l'épreuve des langues rares : expériences de reconnaissance de mots sur la langue japhug (sino-tibétain)

Guillaume, S., Wisniewski, G., Macaire, C., Jacques, G., Michaud, A., Galliot, B., Coavoux, M., Rossato, S., Nguyễn, M., & Fily, M. (2022) · Journées d'Études sur la Parole (JEP) · doi:10.21437/jep.2022-52

Leveraging Language Embeddings for Cross-Lingual Self-Supervised Speech Representation Learning

Tanaka, T., Masumura, R., Ihori, M., Sato, H. P., Yamane, T., Ashihara, T., Matsuura, K., & Moriya, T. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096681

Speech Emotion Recognition in Italian Using Wav2Vec 2Preprint

Catania, F. (2023) · doi:10.36227/techrxiv.22821992.v1 · Cited by 3

XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

Babu, A., Wang, C., Tjandra, A., Lakhotia, K., Xu, Q., Goyal, N., Singh, K., von Platen, P., Saraf, Y., Pino, J., et al. (2022) · Interspeech 2022 · doi:10.21437/interspeech.2022-143 · Cited by 586

Discrete vs Continuous Audio Token Representations in Cross-Lingual Transfer Accuracy on CommonVoice Low-Resource Benchmark

Kernel, S. R. (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.20651351

Language Adaptive Cross-Lingual Speech Representation Learning with Sparse Sharing Sub-Networks

Lu, Y., Huang, M., Qu, X., Wei, P., & Ma, Z. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9747671 · Cited by 16

DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model

Wang, H., Wang, S., Zhang, W.-Q., & Bai, J. (2023) · Interspeech (USB) · doi:10.21437/interspeech.2023-1444 · Cited by 2

Cross-Lingual Self-training to Learn Multilingual Representation for Low-Resource Speech Recognition

Zhang, Z., Song, Y., Wu, M., Fang, X., McLoughlin, I. V., & Dai, L.-R. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02075-7 · Cited by 35