Papers by Leibny Paola Garcia Perera
Where are you from? Geolocating Speech and Applications to Language Identification (2024.naacl-long)
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Patrick Foley, Matthew Wiesner, Bismarck Odoom, Leibny Paola Garcia Perera, Kenton Murray, Philipp Koehn
| Challenge: | Language identification (LID) is a critical component in many modern multilingual speech technologies. |
| Approach: | They propose to use radio broadcasts with known origin to train regression models . they also propose to explore using geolocation as a proxy task for LID . |
| Outcome: | The proposed model outperforms pretrained models on the FLEURS benchmark and on the VoxLingua benchmark. |
Speaking in Wavelet Domain: A Simple and Efficient Approach to Speed up Speech Diffusion Model (2024.emnlp-main)
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Xiangyu Zhang, Daijiao Liu, Hexin Liu, Qiquan Zhang, Hanyu Meng, Leibny Paola Garcia Perera, EngSiong Chng, Lina Yao
| Challenge: | Existing approaches to enhance inference speed and training require complex modifications to the model. |
| Approach: | They propose to double the training and inference speed of Denoising Diffusion Probabilistic Models by simply redirecting the generative target to the wavelet domain. |
| Outcome: | The proposed method doubles the training and inference speed of Speech DDPMs by redirecting the generative target to the wavelet domain. |
CSPB: Conversational Speech Processing Benchmark for Self-supervised Speech Models (2026.eacl-long)
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| Challenge: | Existing benchmarks focus on clean, single-speaker, single channel audio, failing to reflect the complexities of natural human interaction. |
| Approach: | They propose a benchmark to assess the robustness of self-supervised speech models in conversational settings. |
| Outcome: | The proposed benchmark assesses the robustness of self-supervised speech models in conversational scenarios. |