6 papers · 1 filter
Harness TTS: Towards Context-Aware Expressive Speech Synthesis with Harness Layer
Shengfan Shen, Di Wu, Xingchen Song +5
Expressive speech synthesis for voice assistants requires flexible style control that adapts to explicit requests and broader interaction context. We propose Harness TTS, a lightwe…
F3-Tokenizer: Taming Audio Autoencoder Latents for Understanding and Generation
Dinghao Zhou, Xingchen Song, Di Wu +3
Continuous audio autoencoders reconstruct waveforms well but often produce latents with weak structure for understanding, while self-supervised audio encoders capture semantics but…
Borderless Long Speech Synthesis
Xingchen Song, Di Wu, Dinghao Zhou +12
Most existing text-to-speech (TTS) systems either synthesize speech sentence by sentence and stitch the results together, or drive synthesis from plain-text dialogues alone. Both a…
Iterate to Differentiate: Enhancing Discriminability and Reliability in Zero-Shot TTS Evaluation
Shengfan Shen, Di Wu, Xingchen Song +5
Reliable evaluation of modern zero-shot text-to-speech (TTS) models remains challenging. Subjective tests are costly and hard to reproduce, while objective metrics often saturate,…
Adapting Whisper for Streaming Speech Recognition via Two-Pass Decoding
Haoran Zhou, Xingchen Song, Brendan Fahy +9
OpenAI Whisper is a family of robust Automatic Speech Recognition (ASR) models trained on 680,000 hours of audio. However, its encoder-decoder architecture, trained with a sequence…
TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch
Xingchen Song, Mengtao Xing, Changwei Ma +9
It is well known that LLM-based systems are data-hungry. Recent LLM-based TTS works typically employ complex data processing pipelines to obtain high-quality training data. These s…