| Pre-training on high-resource speech recognition improves low-resource speech-to-text translation S Bansal, H Kamper, K Livescu, A Lopez, S Goldwater arXiv preprint arXiv:1809.01431, 2018 | 204 | 2018 |
| Deep convolutional acoustic word embeddings using word-pair side information H Kamper, W Wang, K Livescu IEEE ICASSP, 2016 | 187 | 2016 |
| Participatory research for low-resourced machine translation: A case study in african languages W Nekoto, V Marivate, T Matsila, T Fasubaa, T Kolawole, T Fagbohungbe, ... arXiv preprint arXiv:2010.02353, 2020 | 155 | 2020 |
| Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages W Nekoto, V Marivate, T Matsila, T Fasubaa, T Kolawole, T Fagbohungbe, ... EMNLP Findings, 2020 | 155 | 2020 |
| Unsupervised neural network based feature extraction using weak top-down constraints H Kamper, M Elsner, A Jansen, S Goldwater IEEE ICASSP, 2015 | 138 | 2015 |
| Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge B van Niekerk, L Nortje, H Kamper arXiv preprint arXiv:2005.09409, 2020 | 131 | 2020 |
| A segmental framework for fully-unsupervised large-vocabulary speech recognition H Kamper, A Jansen, S Goldwater Computer Speech & Language, 2017 | 126 | 2017 |
| A comparison of neural network methods for unsupervised representation learning on the Zero Resource Speech Challenge D Renshaw, H Kamper, A Jansen, S Goldwater Interspeech, 2015 | 112 | 2015 |
| An embedded segmental k-means model for unsupervised segmentation and clustering of speech H Kamper, K Livescu, S Goldwater IEEE ASRU, 719-726, 2017 | 109 | 2017 |
| Unsupervised word segmentation and lexicon discovery using acoustic word embeddings H Kamper, A Jansen, S Goldwater IEEE Transactions on Audio, Speech, and Language Processing, 2016 | 102 | 2016 |
| Query-by-Example Search with Discriminative Neural Acoustic Word Embeddings S Settle, K Levin, H Kamper, K Livescu arXiv preprint arXiv:1706.03818, 2017 | 94 | 2017 |
| Towards speech-to-text translation without speech recognition S Bansal, H Kamper, A Lopez, S Goldwater arXiv preprint arXiv:1702.03856, 2017 | 78 | 2017 |
| Truly unsupervised acoustic word embeddings using weak top-down constraints in encoder-decoder models H Kamper ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 76 | 2019 |
| Low-Resource Speech-to-Text Translation S Bansal, H Kamper, K Livescu, A Lopez, S Goldwater arXiv preprint arXiv:1803.09164, 2018 | 70 | 2018 |
| A comparison of discrete and soft speech units for improved voice conversion B van Niekerk, MA Carbonneau, J Zaïdi, M Baas, H Seuté, H Kamper ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 69 | 2022 |
| Visually grounded learning of keyword prediction from untranscribed speech H Kamper, S Settle, G Shakhnarovich, K Livescu arXiv preprint arXiv:1703.08136, 2017 | 66 | 2017 |
| Masakhane--Machine Translation For Africa I Orife, J Kreutzer, B Sibanda, D Whitenack, K Siminyu, L Martinus, JT Ali, ... arXiv preprint arXiv:2003.11529, 2020 | 61 | 2020 |
| Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks R Eloff, A Nortje, B van Niekerk, A Govender, L Nortje, A Pretorius, ... arXiv preprint arXiv:1904.07556, 2019 | 59 | 2019 |
| Semantic Speech Retrieval With a Visually Grounded Model of Untranscribed Speech. H Kamper, G Shakhnarovich, K Livescu IEEE/ACM Transactions on Audio, Speech and Language Processing 27 (1), 89-98, 2019 | 59 | 2019 |
| Fully unsupervised small-vocabulary speech recognition using a segmental Bayesian model H Kamper, A Jansen, S Goldwater Interspeech, 2015 | 47 | 2015 |
Sharon GoldwaterSchool of Informatics, University of Edinburgh在 inf.ed.ac.uk 的电子邮件经过验证
