4 citations · 15 across the 12 of their papers we have counts for
13 papers
Qwen-Audio-3.1-ASR Technical Report
Chuanmeng Bian, Daren Chen, Peixin Chen +45
We present Qwen-Audio-3.1-ASR, a family of audio-language models that builds upon its predecesor Qwen-Audio-3.0-ASR with improved speech recognition and expanded capabilities in sp…
Qwen-Audio-3.0-Gen-Preview Technical Report
Junyu Dai, Xiaoyue Duan, Xinyue Fan +14
Existing single-domain and multi-task audio systems remain limited in directly organizing heterogeneous audio components, ambience, and multiple roles into long-form temporal scene…
VoxRole: A Comprehensive Benchmark for Evaluating Speech-Based Role-Playing Agents
Weihao Wu, Liang Cao, Xinyu Wu +4
Recent significant advancements in Large Language Models (LLMs) have greatly propelled the development of Role-Playing Conversational Agents (RPCAs). These systems aim to create im…
DiffCSS: Diverse and Expressive Conversational Speech Synthesis with Diffusion Models
Weihao wu, Zhiwei Lin, Yixuan Zhou +6
Conversational speech synthesis (CSS) aims to synthesize both contextually appropriate and expressive speech, and considerable efforts have been made to enhance the understanding o…
DiCLET-TTS: Diffusion Model based Cross-lingual Emotion Transfer for Text-to-Speech -- A Study between English and Mandarin
Tao Li, Chenxu Hu, Jian Cong +5
While the performance of cross-lingual TTS based on monolingual corpora has been significantly improved recently, generating cross-lingual speech still suffers from the foreign acc…
Joint Multi-scale Cross-lingual Speaking Style Transfer with Bidirectional Attention Mechanism for Automatic Dubbing
Jingbei Li, Sipan Li, Ping Chen +7
Automatic dubbing, which generates a corresponding version of the input speech in another language, could be widely utilized in many real-world scenarios such as video and game loc…
NeuFA: Neural Network Based End-to-End Forced Alignment with Bidirectional Attention Mechanism
Jingbei Li, Yi Meng, Zhiyong Wu +4
Although deep learning and end-to-end models have been widely used and shown superiority in automatic speech recognition (ASR) and text-to-speech (TTS) synthesis, state-of-the-art…
Enhancing Speaking Styles in Conversational Text-to-Speech Synthesis with Graph-based Multi-modal Context Modeling
Jingbei Li, Yi Meng, Chenyi Li +4
Comparing with traditional text-to-speech (TTS) systems, conversational TTS systems are required to synthesize speeches with proper speaking style confirming to the conversational…
Towards Multi-Scale Style Control for Expressive Speech Synthesis
Xiang Li, Changhe Song, Jingbei Li +3
This paper introduces a multi-scale speech style modeling method for end-to-end expressive speech synthesis. The proposed method employs a multi-scale reference encoder to extract…
Enhancing Word-Level Semantic Representation via Dependency Structure for Expressive Text-to-Speech Synthesis
Yixuan Zhou, Changhe Song, Jingbei Li +4
Exploiting rich linguistic information in raw text is crucial for expressive text-to-speech (TTS). As large scale pre-trained text representation develops, bidirectional encoder re…
Adversarially learning disentangled speech representations for robust multi-factor voice conversion
Jie Wang, Jingbei Li, Xintao Zhao +3
Factorizing speech as disentangled speech representations is vital to achieve highly controllable style transfer in voice conversion (VC). Conventional speech representation learni…
Syntactic representation learning for neural network based TTS with syntactic parse tree traversal
Changhe Song, Jingbei Li, Yixuan Zhou +2
Syntactic structure of a sentence text is correlated with the prosodic structure of the speech that is crucial for improving the prosody and naturalness of a text-to-speech (TTS) s…
Emotion controllable speech synthesis using emotion-unlabeled dataset with the assistance of cross-domain speech emotion recognition
Xiong Cai, Dongyang Dai, Zhiyong Wu +3
Neural text-to-speech (TTS) approaches generally require a huge number of high quality speech data, which makes it difficult to obtain such a dataset with extra emotion labels. In…