SLP-P2.8
SCORE: SELF-SUPERVISED CORRESPONDENCE FINE-TUNING FOR IMPROVED CONTENT REPRESENTATIONS
Amit Meghanani, Thomas Hain, The University of Sheffield, United Kingdom of Great Britain and Northern Ireland
Session:
SLP-P2: Self-supervised learning for speech processing II Poster
Track:
Speech and Language Processing
Location:
Poster Zone 1C
Poster Board PZ-1C.8
Poster Board PZ-1C.8
Presentation Time:
Tue, 16 Apr, 16:30 - 18:30 (UTC +9)
Session Chair:
Soumi Maiti, CMU
Session SLP-P2
SLP-P2.1: Large Scale Self-Supervised Pretraining for Active Speaker Detection
Otavio Braga, Wei Xia, Keith Johnson, Alice Chuang, Yunfan Ye, Olivier Siohan, Tuan Nguyen, Google, United States of America
SLP-P2.2: STAR: DISTILLING SPEECH TEMPORAL RELATION FOR LIGHTWEIGHT SPEECH SELF-SUPERVISED LEARNING MODELS
Kangwook Jang, Sungnyun Kim, Hoirin Kim, KAIST, Korea, Republic of
SLP-P2.3: DATA DRIVEN GRAPHEME-TO-PHONEME REPRESENTATIONS FOR A LEXICON-FREE TEXT-TO-SPEECH
Abhinav Garg, Stanford University, United States of America; Jiyeon Kim, Samsung Research, Korea, Republic of; Sushil Khyalia, Carnegie Mellon University, United States of America; Chanwoo Kim, Korea University, Korea, Republic of; Dhananjaya Gowda, Samsung Research, Korea, Republic of
SLP-P2.4: SELF-SUPERVISED ADAPTIVE PRE-TRAINING OF MULTILINGUAL SPEECH MODELS FOR LANGUAGE AND DIALECT IDENTIFICATION
Mohammed Maqsood Shaik, Dietrich Klakow, Badr Abdullah, Saarland University, Germany
SLP-P2.5: BOOTSTRAP PREDICTIVE CODING: INVESTIGATING A NON-CONTRASTIVE SELF-SUPERVISED LEARNING APPROACH
Yumnah Mohamied, Peter Bell, University of Edinburgh, United Kingdom of Great Britain and Northern Ireland
SLP-P2.6: HUBERTOPIC: ENHANCING SEMANTIC REPRESENTATION OF HUBERT THROUGH SELF-SUPERVISION UTILIZING TOPIC MODEL
Takashi Maekaku, Yahoo Japan Corporation, Japan; Jiatong Shi, Xuankai Chang, Carnegie Mellon University, United States of America; Yuya Fujita, Yahoo Japan Corporation, Japan; Shinji Watanabe, Carnegie Mellon University, United States of America
SLP-P2.7: SD-HUBERT: SENTENCE-LEVEL SELF-DISTILLATION INDUCES SYLLABIC ORGANIZATION IN HUBERT
Cheol Jun Cho, UC Berkeley, United States of America; Abdelrahman Mohamed, Rembrand, United States of America; Shang-Wen Li, Meta, United States of America; Alan W Black, Carnegie Mellon University, United States of America; Gopala K. Anumanchipalli, UC Berkeley, United States of America
SLP-P2.8: SCORE: SELF-SUPERVISED CORRESPONDENCE FINE-TUNING FOR IMPROVED CONTENT REPRESENTATIONS
Amit Meghanani, Thomas Hain, The University of Sheffield, United Kingdom of Great Britain and Northern Ireland
SLP-P2.9: ENHANCING PRE-TRAINED ASR SYSTEM FINE-TUNING FOR DYSARTHRIC SPEECH RECOGNITION USING ADVERSARIAL DATA AUGMENTATION
Huimeng Wang, Zengrui Jin, Mengzhe Geng, Shujie Hu, Guinan Li, Tianzi Wang, Haoning Xu, Xunying Liu, The Chinese University of Hong Kong, Hong Kong
SLP-P2.10: LEARNING CONTEXTUALIZED REPRESENTATION ON DISCRETE SPACE VIA HIERARCHICAL PRODUCT QUANTIZATION
HYUNG YONG KIM, BYEONG-YEOL KIM, YUNKYU Lim, JIHWAN PARK, JINSEOK PARK, YOUSHIN LIM, SEUNG WOO YU, HANBIN LEE, 42dot.ai, Korea, Republic of
SLP-P2.11: Self-supervised Speaker Verification Employing a Novel Clustering Algorithm
Abderrahim Fathan, Jahangir Alam, Computer Research Institute of Montreal (CRIM), Canada
SLP-P2.12: Representation Learning With Hidden Unit Clustering For Low Resource Speech Applications
Varun Krishna, Tarun Sai, Sriram Ganapathy, Indian Institute of Science, India
Contacts