34 citations · 116 across the 19 of their papers we have counts for
12 papers · 1 filter
CoAVT: A Cognition-Inspired Unified Audio-Visual-Text Pre-Training Model for Multimodal Processing
Xianghu Yue, Xiaohai Tian, Lu Lu +3
There has been a long-standing quest for a unified audio-visual-text model to enable various multimodal understanding tasks, which mimics the listening, seeing and reading process…
Leveraging phone-level linguistic-acoustic similarity for utterance-level pronunciation scoring
Wei Liu, Kaiqi Fu, Xiaohai Tian +4
Recent studies on pronunciation scoring have explored the effect of introducing phone embeddings as reference pronunciation, but mostly in an implicit manner, i.e., addition or con…
An ASR-free Fluency Scoring Approach with Self-Supervised Learning
Wei Liu, Kaiqi Fu, Xiaohai Tian +4
A typical fluency scoring system generally relies on an automatic speech recognition (ASR) system to obtain time stamps in input speech for either the subsequent calculation of flu…
TTS-Guided Training for Accent Conversion Without Parallel Data
Yi Zhou, Zhizheng Wu, Mingyang Zhang +2
Accent Conversion (AC) seeks to change the accent of speech from one (source) to another (target) while preserving the speech content and speaker identity. However, many AC approac…
Improving Non-native Word-level Pronunciation Scoring with Phone-level Mixup Data Augmentation and Multi-source Information
Kaiqi Fu, Shaojun Gao, Kai Wang +3
Deep learning-based pronunciation scoring models highly rely on the availability of the annotated non-native data, which is costly and has scalability issues. To deal with the data…
The Multi-speaker Multi-style Voice Cloning Challenge 2021
Qicong Xie, Xiaohai Tian, Guanghou Liu +9
The Multi-speaker Multi-style Voice Cloning Challenge (M2VoC) aims to provide a common sizable dataset as well as a fair testbed for the benchmarking of the popular voice cloning t…
Predictions of Subjective Ratings and Spoofing Assessments of Voice Conversion Challenge 2020 Submissions
Rohan Kumar Das, Tomi Kinnunen, Wen-Chin Huang +5
The Voice Conversion Challenge 2020 is the third edition under its flagship that promotes intra-lingual semiparallel and cross-lingual voice conversion (VC). While the primary eval…
Voice Conversion Challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion
Yi Zhao, Wen-Chin Huang, Xiaohai Tian +5
The voice conversion challenge is a bi-annual scientific event held to compare and understand different voice conversion (VC) systems built on a common dataset. In 2020, we organiz…
The Attacker's Perspective on Automatic Speaker Verification: An Overview
Rohan Kumar Das, Xiaohai Tian, Tomi Kinnunen +1
Security of automatic speaker verification (ASV) systems is compromised by various spoofing attacks. While many types of non-proactive attacks (and their defenses) have been studie…
Black-box Attacks on Automatic Speaker Verification using Feedback-controlled Voice Conversion
Xiaohai Tian, Rohan Kumar Das, Haizhou Li
Automatic speaker verification (ASV) systems in practice are greatly vulnerable to spoofing attacks. The latest voice conversion technologies are able to produce perceptually natur…
A Modularized Neural Network with Language-Specific Output Layers for Cross-lingual Voice Conversion
Yi Zhou, Xiaohai Tian, Emre Yılmaz +2
This paper presents a cross-lingual voice conversion framework that adopts a modularized neural network. The modularized neural network has a common input structure that is shared…
A Vocoder-free WaveNet Voice Conversion with Non-Parallel Data
Xiaohai Tian, Eng Siong Chng, Haizhou Li
In a typical voice conversion system, vocoder is commonly used for speech-to-features analysis and features-to-speech synthesis. However, vocoder can be a source of speech quality…