Nityanand Mathur
PulseAugur coverage of Nityanand Mathur — every cluster mentioning Nityanand Mathur across labs, papers, and developer communities, ranked by signal.
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DLLM-TTS framework enables faster, more accurate text-to-speech synthesis
Researchers have introduced DLLM-TTS, a novel text-to-speech synthesis framework that addresses the trade-off between speech intelligibility and generation speed. This new approach formulates TTS as conditional block di…
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New method reveals how style instructions shape text-to-speech output
Researchers have developed a new method to understand how natural language instructions influence the output of style-captioned text-to-speech (TTS) systems. By adapting the DAAM framework to speech diffusion models, th…
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FlowEdit enables lifelong pronunciation adaptation in TTS models
Researchers have developed FlowEdit, a novel framework designed to adapt frozen flow-matching text-to-speech (TTS) systems for lifelong pronunciation correction. Instead of retraining the entire model, FlowEdit learns p…