Automatic Speech Recognition
Automatic Speech Recognition (ASR) aims to accurately transcribe spoken language into text, driving research into robust and efficient models. Current efforts focus on improving accuracy and robustness through techniques like consistency regularization in Connectionist Temporal Classification (CTC), leveraging pre-trained multilingual models for low-resource languages, and integrating Large Language Models (LLMs) for enhanced contextual understanding and improved handling of diverse accents and speech disorders. These advancements have significant implications for accessibility, enabling applications in diverse fields such as healthcare, education, and human-computer interaction.
Papers
Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm
Weiran Wang, Zelin Wu, Diamantino Caseiro, Tsendsuren Munkhdalai, Khe Chai Sim, Pat Rondon, Golan Pundak, Gan Song, Rohit Prabhavalkar, Zhong Meng, Ding Zhao, Tara Sainath, Pedro Moreno Mengibar
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections through Federated Learning
Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews
Federated Learning with Differential Privacy for End-to-End Speech Recognition
Martin Pelikan, Sheikh Shams Azam, Vitaly Feldman, Jan "Honza" Silovsky, Kunal Talwar, Tatiana Likhomanenko
Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customization
Alexandra Antonova
Exploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Study
Xuankai Chang, Brian Yan, Kwanghee Choi, Jeeweon Jung, Yichen Lu, Soumi Maiti, Roshan Sharma, Jiatong Shi, Jinchuan Tian, Shinji Watanabe, Yuya Fujita, Takashi Maekaku, Pengcheng Guo, Yao-Fei Cheng, Pavel Denisov, Kohei Saijo, Hsiu-Hsuan Wang
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
Chen Chen, Yuchen Hu, Chao-Han Huck Yang, Sabato Macro Siniscalchi, Pin-Yu Chen, Eng Siong Chng
Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference
Masao Someki, Nicholas Eng, Yosuke Higuchi, Shinji Watanabe
Learning from Flawed Data: Weakly Supervised Automatic Speech Recognition
Dongji Gao, Hainan Xu, Desh Raj, Leibny Paola Garcia Perera, Daniel Povey, Sanjeev Khudanpur
Connecting Speech Encoder and Large Language Model for ASR
Wenyi Yu, Changli Tang, Guangzhi Sun, Xianzhao Chen, Tian Tan, Wei Li, Lu Lu, Zejun Ma, Chao Zhang
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data
Jianwei Yu, Hangting Chen, Yanyao Bian, Xiang Li, Yi Luo, Jinchuan Tian, Mengyang Liu, Jiayi Jiang, Shuai Wang
Cross-modal Alignment with Optimal Transport for CTC-based ASR
Xugang Lu, Peng Shen, Yu Tsao, Hisashi Kawai
The second multi-channel multi-party meeting transcription challenge (M2MeT) 2.0): A benchmark for speaker-attributed ASR
Yuhao Liang, Mohan Shi, Fan Yu, Yangze Li, Shiliang Zhang, Zhihao Du, Qian Chen, Lei Xie, Yanmin Qian, Jian Wu, Zhuo Chen, Kong Aik Lee, Zhijie Yan, Hui Bu
Memory-augmented conformer for improved end-to-end long-form ASR
Carlos Carvalho, Alberto Abad
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model
Jiamin Xie, Ke Li, Jinxi Guo, Andros Tjandra, Yuan Shangguan, Leda Sari, Chunyang Wu, Junteng Jia, Jay Mahadeokar, Ozlem Kalinli
Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR
Sheikh Shams Azam, Tatiana Likhomanenko, Martin Pelikan, Jan "Honza" Silovsky
Massive End-to-end Models for Short Search Queries
Weiran Wang, Rohit Prabhavalkar, Dongseong Hwang, Qiujia Li, Khe Chai Sim, Bo Li, James Qin, Xingyu Cai, Adam Stooke, Zhong Meng, CJ Zheng, Yanzhang He, Tara Sainath, Pedro Moreno Mengibar
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferences
Hugo Malard, Salah Zaiem, Robin Algayres