23 citations · 28 across the 5 of their papers we have counts for
6 papers
TS-SP: Learning Speaker-Preserving Representations in Audio Large Language Models
Junjie Li, Zheng Liang, Zhe Li +2
Audio large language models (ALLMs) can understand speech content, yet their ability to use speaker identity for verification remains limited. We propose TS-SP (Two-Stage Speaker P…
Text-Independent Speaker Verification Using Discrete Audio Tokens
Zheng Liang, Junjie Li, Kong Aik Lee
Neural audio codecs (NACs) enable efficient audio compression and have achieved success in downstream tasks such as speech synthesis. However, their discrete representations consis…
Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens
Xinsheng Wang, Mingqi Jiang, Ziyang Ma +22
Recent advancements in large language models (LLMs) have driven significant progress in zero-shot text-to-speech (TTS) synthesis. However, existing foundation models rely on multi-…
Incorporating Class-based Language Model for Named Entity Recognition in Factorized Neural Transducer
Peng Wang, Yifan Yang, Zheng Liang +3
Despite advancements of end-to-end (E2E) models in speech recognition, named entity recognition (NER) is still challenging but critical for semantic understanding. Previous studies…
Improving Code-Switching and Named Entity Recognition in ASR with Speech Editing based Data Augmentation
Zheng Liang, Zheshu Song, Ziyang Ma +3
Recently, end-to-end (E2E) automatic speech recognition (ASR) models have made great strides and exhibit excellent performance in general speech recognition. However, there remain…
UniCATS: A Unified Context-Aware Text-to-Speech Framework with Contextual VQ-Diffusion and Vocoding
Chenpeng Du, Yiwei Guo, Feiyu Shen +6
The utilization of discrete speech tokens, divided into semantic tokens and acoustic tokens, has been proven superior to traditional acoustic feature mel-spectrograms in terms of n…