23 citations · 59 across the 12 of their papers we have counts for
12 papers
Luna-TTS Family Technical Report
Feng Yin, Shuai Shi, Junjie Zheng +19
Modern text-to-speech (TTS) is dominated by autoregressive (AR) codec language models, whose left-to-right decoding brings latency that grows with utterance length, error accumulat…
Bagpiper-Edit: Zero-Shot Open-Ended Audio Editing via Rich-Caption
Xun Gong, Jinchuan Tian, Haoran Wang +3
Current text-guided audio editing methods rely on paired training data, predefined operation templates, and separate processing pipelines across speech, music, and sound. We presen…
Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions
Jinchuan Tian, Haoran Wang, Bo-Hao Su +14
Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio rather than the whole. In contra…
UrgentMOS: Unified Multi-Metric and Preference Learning for Robust Speech Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li +12
Automatic speech quality assessment has become increasingly important as modern speech generation systems continue to advance, while human listening tests remain costly, time-consu…
Text adaptation for speaker verification with speaker-text factorized embeddings
Yexin Yang, Shuai Wang, Xun Gong +2
Text mismatch between pre-collected data, either training data or enrollment data, and the actual test data can significantly hurt text-dependent speaker verification (SV) system p…
BR-ASR: Efficient and Scalable Bias Retrieval Framework for Contextual Biasing ASR in Speech LLM
Xun Gong, Anqi Lv, Zhiming Wang +2
While speech large language models (SpeechLLMs) have advanced standard automatic speech recognition (ASR), contextual biasing for named entities and rare words remains challenging,…
Advanced Long-Content Speech Recognition With Factorized Neural Transducer
Xun Gong, Yu Wu, Jinyu Li +4
In this paper, we propose two novel approaches, which integrate long-content information into the factorized neural transducer (FNT) based architecture in both non-streaming (refer…
DQ-Whisper: Joint Distillation and Quantization for Efficient Multilingual Speech Recognition
Hang Shao, Bei Liu, Wei Wang +2
As a popular multilingual and multitask pre-trained speech model, Whisper has the problem of curse of multilinguality. To enhance multilingual capabilities in small Whisper models,…
LongFNT: Long-form Speech Recognition with Factorized Neural Transducer
Xun Gong, Yu Wu, Jinyu Li +4
Traditional automatic speech recognition~(ASR) systems usually focus on individual utterances, without considering long-form speech with useful historical information, which is mor…
SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data
Ziqiang Zhang, Sanyuan Chen, Long Zhou +8
How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this…
Knowledge Transfer and Distillation from Autoregressive to Non-Autoregressive Speech Recognition
Xun Gong, Zhikai Zhou, Yanmin Qian
Modern non-autoregressive~(NAR) speech recognition systems aim to accelerate the inference speed; however, they suffer from performance degradation compared with autoregressive~(AR…
Layer-wise Fast Adaptation for End-to-End Multi-Accent Speech Recognition
Xun Gong, Yizhou Lu, Zhikai Zhou +1
Accent variability has posed a huge challenge to automatic speech recognition~(ASR) modeling. Although one-hot accent vector based adaptation systems are commonly used, they requir…