859 citations · 914 across the 21 of their papers we have counts for
21 papers
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…
Towards General-Purpose Text-Instruction-Guided Voice Conversion
Chun-Yi Kuan, Chen An Li, Tsu-Yuan Hsu +5
This paper introduces a novel voice conversion (VC) model, guided by text instructions such as "articulate slowly with a deep tone" or "speak in a cheerful boyish voice". Unlike tr…
Text Injection for Capitalization and Turn-Taking Prediction in Speech Models
Shaan Bijwadia, Shuo-yiin Chang, Weiran Wang +3
Text injection for automatic speech recognition (ASR), wherein unpaired text-only data is used to supplement paired audio-text data, has shown promising improvements for word error…
Semantic Segmentation with Bidirectional Language Models Improves Long-form ASR
W. Ronny Huang, Hao Zhang, Shankar Kumar +2
We propose a method of segmenting long-form speech by separating semantically complete sentences within the utterance. This prevents the ASR decoder from needlessly processing fara…
UML: A Universal Monolingual Output Layer for Multilingual ASR
Chao Zhang, Bo Li, Tara N. Sainath +2
Word-piece models (WPMs) are commonly used subword units in state-of-the-art end-to-end automatic speech recognition (ASR) systems. For multilingual ASR, due to the differences in…
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…
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…
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 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…
A Better and Faster End-to-End Model for Streaming ASR
Bo Li, Anmol Gulati, Jiahui Yu +12
End-to-end (E2E) models have shown to outperform state-of-the-art conventional models for streaming speech recognition [1] across many dimensions, including quality (as measured by…
FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization
Jiahui Yu, Chung-Cheng Chiu, Bo Li +8
Streaming automatic speech recognition (ASR) aims to emit each hypothesized word as quickly and accurately as possible. However, emitting fast without degrading quality, as measure…
Towards Fast and Accurate Streaming End-to-End ASR
Bo Li, Shuo-yiin Chang, Tara N. Sainath +4
End-to-end (E2E) models fold the acoustic, pronunciation and language models of a conventional speech recognition model into one neural network with a much smaller number of parame…
A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency
Tara N. Sainath, Yanzhang He, Bo Li +26
Thus far, end-to-end (E2E) models have not been shown to outperform state-of-the-art conventional models with respect to both quality, i.e., word error rate (WER), and latency, i.e…
On Neural Phone Recognition of Mixed-Source ECoG Signals
Ahmed Hussen Abdelaziz, Shuo-Yiin Chang, Nelson Morgan +5
The emerging field of neural speech recognition (NSR) using electrocorticography has recently attracted remarkable research interest for studying how human brains recognize speech…
Personal VAD: Speaker-Conditioned Voice Activity Detection
Shaojin Ding, Quan Wang, Shuo-yiin Chang +2
In this paper, we propose "personal VAD", a system to detect the voice activity of a target speaker at the frame level. This system is useful for gating the inputs to a streaming o…
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,…
Streaming End-to-end Speech Recognition For Mobile Devices
Yanzhang He, Tara N. Sainath, Rohit Prabhavalkar +17
End-to-end (E2E) models, which directly predict output character sequences given input speech, are good candidates for on-device speech recognition. E2E models, however, present nu…