SLP-P2: Self-supervised learning for speech processing II
Tue, 16 Apr, 16:30 - 18:30 (UTC +9)
Location: Poster Zone 1C
Session Type: Poster
Session Chair: Soumi Maiti, CMU
Track: Speech and Language Processing
Click the to view the manuscript on IEEE Xplore Open Preview
 

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