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cs.AI2025
Align2Speak: Improving TTS for Low Resource Languages via ASR-Guided Online Preference Optimization
Shehzeen Hussain, Paarth Neekhara, Xuesong Yang +7
Developing high-quality text-to-speech (TTS) systems for low-resource languages is challenging due to the scarcity of paired text and speech data. In contrast, automatic speech rec…
eess.AS2025
Frame-Stacked Local Transformers For Efficient Multi-Codebook Speech Generation
Roy Fejgin, Paarth Neekhara, Xuesong Yang +6
Speech generation models based on large language models (LLMs) typically operate on discrete acoustic codes, which differ fundamentally from text tokens due to their multicodebook…
cs.SD2025
Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Guidance
Shehzeen Hussain, Paarth Neekhara, Xuesong Yang +6
While autoregressive speech token generation models produce speech with remarkable variety and naturalness, their inherent lack of controllability often results in issues such as h…