4 citations · 7 across the 15 of their papers we have counts for
8 papers · 1 filter
Source-Adaptive Data Curation for Bilingual NVV-Aware ASR
Yuang Cao, Qirui Zhan, Jingbin Hu +7
Nonverbal vocalizations (NVVs), such as laughter, sighs, breaths, and coughs, convey affective and interactional information that conventional automatic speech recognition (ASR) sy…
MINT-Bench: A Comprehensive Multilingual Benchmark for Instruction-Following Text-to-Speech
Huakang Chen, Jingbin Hu, Liumeng Xue +12
Instruction-following text-to-speech (TTS) has emerged as an important capability for controllable and expressive speech generation, yet its evaluation remains underdeveloped due t…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…
WenetSpeech4TTS: A 12,800-hour Mandarin TTS Corpus for Large Speech Generation Model Benchmark
Linhan Ma, Dake Guo, Kun Song +7
With the development of large text-to-speech (TTS) models and scale-up of the training data, state-of-the-art TTS systems have achieved impressive performance. In this paper, we pr…
Text-aware and Context-aware Expressive Audiobook Speech Synthesis
Dake Guo, Xinfa Zhu, Liumeng Xue +3
Recent advances in text-to-speech have significantly improved the expressiveness of synthetic speech. However, a major challenge remains in generating speech that captures the dive…
Single-Codec: Single-Codebook Speech Codec towards High-Performance Speech Generation
Hanzhao Li, Liumeng Xue, Haohan Guo +6
The multi-codebook speech codec enables the application of large language models (LLM) in TTS but bottlenecks efficiency and robustness due to multi-sequence prediction. To avoid t…