| Open-Source Conversational AI with SpeechBrain 1.0 M Ravanelli, T Parcollet, A Moumen, S de Langen, C Subakan, ... arXiv preprint arXiv:2407.00463, 2024 | 62 | 2024 |
| On The Usefulness of Self-Attention for Automatic Speech Recognition with Transformers S Zhang, E Loweimi, P Bell, S Renals 2021 IEEE Spoken Language Technology Workshop (SLT), 89-96, 2021 | 58 | 2021 |
| LeBenchmark 2.0: A standardized, replicable and enhanced framework for self-supervised representations of French speech T Parcollet, H Nguyen, S Evain, MZ Boito, A Pupier, S Mdhaffar, H Le, ... Computer Speech & Language, 101622, 2024 | 41 | 2024 |
| SummaryMixing: A linearcomplexity alternative to self-attention for speech recognition and understanding T Parcollet, R van Dalen, S Zhang, S Bhattacharya arXiv preprint arXiv:2307.07421, 2024 | 23 | 2024 |
| Windowed attention mechanisms for speech recognition S Zhang, E Loweimi, P Bell, S Renals ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 23 | 2019 |
| Learning Noise Invariant Features Through Transfer Learning For Robust End-to-End Speech Recognition S Zhang, CT Do, R Doddipatla, S Renals ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 20 | 2020 |
| Stochastic Attention Head Removal: A Simple and Effective Method for Improving Automatic Speech Recognition with Transformers S Zhang, E Loweimi, P Bell, S Renals arXiv e-prints, arXiv: 2011.04004, 2020 | 17* | 2020 |
| Transformer-Based Streaming ASR with Cumulative Attention M Li, S Zhang, C Zorilă, R Doddipatla ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 16 | 2022 |
| On the (In) Efficiency of Acoustic Feature Extractors for Self-Supervised Speech Representation Learning T Parcollet, S Zhang, R van Dalen, AGCP Ramos, S Bhattacharya Interspeech 2023, 2023 | 15 | 2023 |
| Real-Time Personalised Speech Enhancement Transformers with Dynamic Cross-attended Speaker Representations S Zhang, M Chadwick, AGCP Ramos, T Parcollet, R van Dalen, ... | 14* | |
| Trainable Dynamic Subsampling for End-to-End Speech Recognition. S Zhang, E Loweimi, Y Xu, P Bell, S Renals INTERSPEECH, 1413-1417, 2019 | 13 | 2019 |
| Train your classifier first: Cascade Neural Networks Training from upper layers to lower layers S Zhang, CT Do, R Doddipatla, E Loweimi, P Bell, S Renals ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 3* | 2021 |
| Benchmarking Rotary Position Embeddings for Automatic Speech Recognition S Zhang, T Parcollet, R van Dalen, S Bhattacharya arXiv preprint arXiv:2501.06051, 2025 | 2 | 2025 |
| Selective Adaptation of End-to-End Speech Recognition using Hybrid CTC/Attention Architecture for Noise Robustness CT Do, S Zhang, T Hain 2020 28th European Signal Processing Conference (EUSIPCO), 321-325, 2021 | 2 | 2021 |
| Evaluation of LLMs in Speech is Often Flawed: Test Set Contamination in Large Language Models for Speech Recognition Y Tseng, T Parcollet, R van Dalen, S Zhang, S Bhattacharya arXiv preprint arXiv:2505.22251, 2025 | 1 | 2025 |
| Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use T Parcollet, Y Tseng, S Zhang, R van Dalen arXiv preprint arXiv:2505.21578, 2025 | 1 | 2025 |
| Linear-Complexity Self-Supervised Learning for Speech Processing S Zhang, T Parcollet, R van Dalen, S Bhattacharya arXiv preprint arXiv:2407.13377, 2024 | 1 | 2024 |
| Robust Unsupervised Adaptation of a Speech Recogniser Using Entropy Minimisation and Speaker Codes RC van Dalen, S Zhang, T Parcollet, S Bhattacharya arXiv preprint arXiv:2506.10653, 2025 | | 2025 |
| Linear Time Complexity Conformers with SummaryMixing for Streaming Speech Recognition T Parcollet, R van Dalen, S Zhang, S Batthacharya arXiv preprint arXiv:2409.07165, 2024 | | 2024 |
| Resource Efficient Self-Supervised Learning for Speech Embeddings A Mehrotra, AGCP Ramos, S Zhang, S Zaiem, T Parcollet, S Bhattacharya | | |
Titouan ParcolletResearch Scientist, Samsung AI Cambridge - University of CambridgeVerified email at samsung.com
