859 citations · 2.2k across the 80 of their papers we have counts for
18 papers · 1 filter
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion
Zhouyuan Huo, Khe Chai Sim, Bo Li +3
Self-supervised pre-training of a speech foundation model, followed by supervised fine-tuning, has shown impressive quality improvements on automatic speech recognition (ASR) tasks…
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…
E2E Segmentation in a Two-Pass Cascaded Encoder ASR Model
W. Ronny Huang, Shuo-Yiin Chang, Tara N. Sainath +7
We explore unifying a neural segmenter with two-pass cascaded encoder ASR into a single model. A key challenge is allowing the segmenter (which runs in real-time, synchronously wit…
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…
JOIST: A Joint Speech and Text Streaming Model For ASR
Tara N. Sainath, Rohit Prabhavalkar, Ankur Bapna +6
We present JOIST, an algorithm to train a streaming, cascaded, encoder end-to-end (E2E) model with both speech-text paired inputs, and text-only unpaired inputs. Unlike previous wo…
Scaling Up Deliberation for Multilingual ASR
Ke Hu, Bo Li, Tara N. Sainath
Multilingual end-to-end automatic speech recognition models are attractive due to its simplicity in training and deployment. Recent work on large-scale training of such models has…
Streaming End-to-End Multilingual Speech Recognition with Joint Language Identification
Chao Zhang, Bo Li, Tara Sainath +4
Language identification is critical for many downstream tasks in automatic speech recognition (ASR), and is beneficial to integrate into multilingual end-to-end ASR as an additiona…
A Language Agnostic Multilingual Streaming On-Device ASR System
Bo Li, Tara N. Sainath, Ruoming Pang +9
On-device end-to-end (E2E) models have shown improvements over a conventional model on English Voice Search tasks in both quality and latency. E2E models have also shown promising…
Streaming Intended Query Detection using E2E Modeling for Continued Conversation
Shuo-yiin Chang, Guru Prakash, Zelin Wu +7
In voice-enabled applications, a predetermined hotword isusually used to activate a device in order to attend to the query.However, speaking queries followed by a hotword each time…
Turn-Taking Prediction for Natural Conversational Speech
Shuo-yiin Chang, Bo Li, Tara N. Sainath +4
While a streaming voice assistant system has been used in many applications, this system typically focuses on unnatural, one-shot interactions assuming input from a single voice qu…
Improving Deliberation by Text-Only and Semi-Supervised Training
Ke Hu, Tara N. Sainath, Yanzhang He +4
Text-only and semi-supervised training based on audio-only data has gained popularity recently due to the wide availability of unlabeled text and speech data. In this work, we prop…
Self-Supervised Speech Representation Learning: A Review
Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt +9
Although supervised deep learning has revolutionized speech and audio processing, it has necessitated the building of specialist models for individual tasks and application scenari…
Streaming Align-Refine for Non-autoregressive Deliberation
Weiran Wang, Ke Hu, Tara N. Sainath
We propose a streaming non-autoregressive (non-AR) decoding algorithm to deliberate the hypothesis alignment of a streaming RNN-T model. Our algorithm facilitates a simple greedy d…
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…
Improving Rare Word Recognition with LM-aware MWER Training
Weiran Wang, Tongzhou Chen, Tara N. Sainath +10
Language models (LMs) significantly improve the recognition accuracy of end-to-end (E2E) models on words rarely seen during training, when used in either the shallow fusion or the…
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes
Shaojin Ding, Weiran Wang, Ding Zhao +11
In this paper, we propose a dynamic cascaded encoder Automatic Speech Recognition (ASR) model, which unifies models for different deployment scenarios. Moreover, the model can sign…
Sentence-Select: Large-Scale Language Model Data Selection for Rare-Word Speech Recognition
W. Ronny Huang, Cal Peyser, Tara N. Sainath +3
Language model fusion helps smart assistants recognize words which are rare in acoustic data but abundant in text-only corpora (typed search logs). However, such corpora have prope…
Improving the fusion of acoustic and text representations in RNN-T
Chao Zhang, Bo Li, Zhiyun Lu +2
The recurrent neural network transducer (RNN-T) has recently become the mainstream end-to-end approach for streaming automatic speech recognition (ASR). To estimate the output dist…