859 citations · 2.2k across the 80 of their papers we have counts for
6 papers · 1 filter
Improved Long-Form Speech Recognition by Jointly Modeling the Primary and Non-primary Speakers
Guru Prakash Arumugam, Shuo-yiin Chang, Tara N. Sainath +3
ASR models often suffer from a long-form deletion problem where the model predicts sequential blanks instead of words when transcribing a lengthy audio (in the order of minutes or…
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition
Chao-Han Huck Yang, Bo Li, Yu Zhang +4
In this work, we propose a new parameter-efficient learning framework based on neural model reprogramming for cross-lingual speech recognition, which can \textbf{re-purpose} well-t…
A Quantum Kernel Learning Approach to Acoustic Modeling for Spoken Command Recognition
Chao-Han Huck Yang, Bo Li, Yu Zhang +4
We propose a quantum kernel learning (QKL) framework to address the inherent data sparsity issues often encountered in training large-scare acoustic models in low-resource scenario…
Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems
Shaan Bijwadia, Shuo-yiin Chang, Bo Li +3
Automatic speech recognition (ASR) systems typically rely on an external endpointer (EP) model to identify speech boundaries. In this work, we propose a method to jointly train the…
E2E Segmenter: Joint Segmenting and Decoding for Long-Form ASR
W. Ronny Huang, Shuo-yiin Chang, David Rybach +5
Improving the performance of end-to-end ASR models on long utterances ranging from minutes to hours in length is an ongoing challenge in speech recognition. A common solution is to…
Deep Learning for Audio Signal Processing
Hendrik Purwins, Bo Li, Tuomas Virtanen +3
Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing. Speech, music,…