4 citations · 13 across the 14 of their papers we have counts for
14 papers
Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignment
Xiang Li, Yixuan Zhou, Jingran Xie +2
Neural speech codecs based on Vector-Quantized VAEs (VQ-VAEs) are core audio tokenizers for speech LLMs, yet their reconstruction fidelity is bottlenecked by quantization error. Mo…
Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
Qiushi Sun, Zhangyue Yin, Xiang Li +3
Large Language Models (LLMs) are evolving at an unprecedented pace and have exhibited considerable capability in the realm of natural language processing (NLP) with world knowledge…
A Discourse-level Multi-scale Prosodic Model for Fine-grained Emotion Analysis
Xianhao Wei, Jia Jia, Xiang Li +2
This paper explores predicting suitable prosodic features for fine-grained emotion analysis from the discourse-level text. To obtain fine-grained emotional prosodic features as pre…
SnakeGAN: A Universal Vocoder Leveraging DDSP Prior Knowledge and Periodic Inductive Bias
Sipan Li, Songxiang Liu, Luwen Zhang +5
Generative adversarial network (GAN)-based neural vocoders have been widely used in audio synthesis tasks due to their high generation quality, efficient inference, and small compu…
CALM: Contrastive Cross-modal Speaking Style Modeling for Expressive Text-to-Speech Synthesis
Yi Meng, Xiang Li, Zhiyong Wu +6
To further improve the speaking styles of synthesized speeches, current text-to-speech (TTS) synthesis systems commonly employ reference speeches to stylize their outputs instead o…
Lexical Speaker Error Correction: Leveraging Language Models for Speaker Diarization Error Correction
Rohit Paturi, Sundararajan Srinivasan, Xiang Li
Speaker diarization (SD) is typically used with an automatic speech recognition (ASR) system to ascribe speaker labels to recognized words. The conventional approach reconciles out…
Diverse and Expressive Speech Prosody Prediction with Denoising Diffusion Probabilistic Model
Xiang Li, Songxiang Liu, Max W. Y. Lam +3
Expressive human speech generally abounds with rich and flexible speech prosody variations. The speech prosody predictors in existing expressive speech synthesis methods mostly pro…
Towards Cross-speaker Reading Style Transfer on Audiobook Dataset
Xiang Li, Changhe Song, Xianhao Wei +3
Cross-speaker style transfer aims to extract the speech style of the given reference speech, which can be reproduced in the timbre of arbitrary target speakers. Existing methods on…
Lexical Knowledge Internalization for Neural Dialog Generation
Zhiyong Wu, Wei Bi, Xiang Li +2
We propose knowledge internalization (KI), which aims to complement the lexical knowledge into neural dialog models. Instead of further conditioning the knowledge-grounded dialog (…
Content-Dependent Fine-Grained Speaker Embedding for Zero-Shot Speaker Adaptation in Text-to-Speech Synthesis
Yixuan Zhou, Changhe Song, Xiang Li +5
Zero-shot speaker adaptation aims to clone an unseen speaker's voice without any adaptation time and parameters. Previous researches usually use a speaker encoder to extract a glob…
An End-to-end Chinese Text Normalization Model based on Rule-guided Flat-Lattice Transformer
Wenlin Dai, Changhe Song, Xiang Li +4
Text normalization, defined as a procedure transforming non standard words to spoken-form words, is crucial to the intelligibility of synthesized speech in text-to-speech system. R…
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation
Zhiyong Wu, Lingpeng Kong, Wei Bi +2
A neural multimodal machine translation (MMT) system is one that aims to perform better translation by extending conventional text-only translation models with multimodal informati…
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…
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…