| Segmental contrastive predictive coding for unsupervised word segmentation S Bhati, J Villalba, P Żelasko, L Moro-Velazquez, N Dehak arXiv preprint arXiv:2106.02170, 2021 | 64 | 2021 |
| LSTM Siamese network for Parkinson’s disease detection from speech S Bhati, LM Velazquez, J Villalba, N Dehak 2019 ieee global conference on signal and information processing (globalsip …, 2019 | 38 | 2019 |
| Unsupervised speech segmentation and variable rate representation learning using segmental contrastive predictive coding S Bhati, J Villalba, P Żelasko, L Moro-Velazquez, N Dehak IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 2002-2014, 2022 | 36 | 2022 |
| Self-expressing autoencoders for unsupervised spoken term discovery S Bhati, J Villalba, P Żelasko, N Dehak arXiv preprint arXiv:2007.13033, 2020 | 27 | 2020 |
| Discovering phonetic inventories with crosslingual automatic speech recognition P Żelasko, S Feng, LM Velazquez, A Abavisani, S Bhati, O Scharenborg, ... Computer speech & language 74, 101358, 2022 | 22 | 2022 |
| Unsupervised Speech Signal to Symbol Transformation for Zero Resource Speech Applications. S Bhati, S Nayak, KSR Murty Interspeech, 2133-2137, 2017 | 22 | 2017 |
| Omni-R1: Do You Really Need Audio to Fine-Tune Your Audio LLM? A Rouditchenko, S Bhati, E Araujo, S Thomas, H Kuehne, R Feris, J Glass arXiv preprint arXiv:2505.09439, 2025 | 21 | 2025 |
| Phoneme based embedded segmental k-means for unsupervised term discovery S Bhati, H Kamper, KSR Murty 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 17 | 2018 |
| An investigation into instantaneous frequency estimation methods for improved speech recognition features S Nayak, S Bhati, KSR Murty 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2017 | 15 | 2017 |
| Unsupervised Acoustic Segmentation and Clustering Using Siamese Network Embeddings. S Bhati, S Nayak, KSR Murty, N Dehak INTERSPEECH, 2668-2672, 2019 | 14 | 2019 |
| Unsupervised segmentation of speech signals using kernel-gram matrices S Bhati, S Nayak, K Sri Rama Murty National Conference on Computer Vision, Pattern Recognition, Image …, 2017 | 11 | 2017 |
| DASS: Distilled audio state space models are stronger and more duration-scalable learners S Bhati, Y Gong, L Karlinsky, H Kuehne, R Feris, J Glass 2024 IEEE Spoken Language Technology Workshop (SLT), 1015-1022, 2024 | 9 | 2024 |
| Audio-visual neural syntax acquisition CIJ Lai, F Shi, P Peng, Y Kim, K Gimpel, S Chang, YS Chuang, S Bhati, ... 2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 1-8, 2023 | 9 | 2023 |
| Modeling sparse spatio-temporal representations for no-reference video quality assessment PM Shabeer, S Bhati, SS Channappayya 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2017 | 9 | 2017 |
| Unsupervised speech signal-to-symbol transformation for language identification S Bhati, S Nayak, SRM Kodukula Circuits, Systems, and Signal Processing 39 (10), 5169-5197, 2020 | 6 | 2020 |
| USAD: Universal Speech and Audio Representation via Distillation HJ Chang, S Bhati, J Glass, AH Liu arXiv preprint arXiv:2506.18843, 2025 | 5 | 2025 |
| Segmental SpeechCLIP: Utilizing Pretrained Image-text Models for Audio-Visual Learning S Bhati, J Villalba, L Moro-Velazquez, T Thebaud, N Dehak Interspeech, 431-435, 2023 | 5 | 2023 |
| State-space large audio language models S Bhati, Y Gong, L Karlinsky, H Kuehne, R Feris, J Glass arXiv preprint arXiv:2411.15685, 2024 | 4 | 2024 |
| Leveraging pretrained image-text models for improving audio-visual learning S Bhati, J Villalba, L Moro-Velazquez, T Thebaud, N Dehak arXiv preprint arXiv:2309.04628, 2023 | 4 | 2023 |
| Zero resource speaking rate estimation from change point detection of syllable-like units S Nayak, S Bhati, KSR Murty ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 4 | 2019 |
Najim DehakAssociate Professor at ECE department, Johns Hopkins University.Verified email at jhu.edu
