{"url":"/method/pase","slug":"pase","name":"PASE+","full_name":"Problem Agnostic Speech Encoder +","full_name_withheld":false,"description_markdown":"**PASE+** is a problem-agnostic speech encoder that combines a convolutional encoder followed by multiple neural networks, called workers, tasked to solve self-supervised problems (i.e., ones that do not require manual annotations as ground truth). An online speech distortion module is employed, that contaminates the input signals with a variety of random disturbances. A revised encoder is also proposed that better learns short- and long-term speech dynamics with an efficient combination of recurrent and convolutional networks. Finally, the authors refine the set of workers used in self-supervision to encourage better cooperation.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Multi-task self-supervised learning for Robust Speech Recognition","paper":"/paper/multi-task-self-supervised-learning-for-1","first_author":"Mirco Ravanelli","n_authors":7,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/multi-task-self-supervised-learning-for-1"},"source":{"url":"https://arxiv.org/abs/2001.09239v2","title":"Multi-task self-supervised learning for Robust Speech Recognition","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Self-Supervised Learning","url":"/methods/category/self-supervised-learning","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":"/paper/perceptual-loss-based-speech-denoising-with","title":"Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised Models","date":"2020-10-22","arxiv_id":"2010.11860","n_code_links":1,"syntology":null},{"paper":"/paper/multi-task-self-supervised-learning-for-1","title":"Multi-task self-supervised learning for Robust Speech Recognition","date":"2020-01-25","arxiv_id":"2001.09239","n_code_links":1,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/denoising","name":"Denoising","papers":1},{"task":"/task/emotion-classification","name":"Emotion Classification","papers":1},{"task":"/task/multi-task-learning","name":"Multi-Task Learning","papers":1},{"task":"/task/robust-speech-recognition","name":"Robust Speech Recognition","papers":1},{"task":"/task/self-supervised-learning","name":"Self-Supervised Learning","papers":1},{"task":"/task/speech-denoising","name":"Speech Denoising","papers":1},{"task":"/task/speech-recognition","name":"Speech Recognition","papers":1},{"task":"/task/speech-recognition-1","name":"speech-recognition","papers":1}],"tasks_shown":8,"n_tasks":8,"usage_by_year":[{"year":"2020","papers":2}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/pase"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}