Pronouncing Hard Words: Phoneme Adaptation of a Pretrained Conversational Text to Speech Model
Voice agents built as cascaded automatic speech recognition (ASR)->large language model (LLM)-> text-to-speech (TTS) pipelines increasingly rely on conversational TTS: streaming, context conditioned models that adapt delivery to dialogue history. Such models are natural and expressive but offer little explicit control over how rare, trust-critical drug names are pronounced, because these entities are too infrequent, and their vocabulary too fast-growing, to be covered by any amount of pre-, mid-, or post-training. We retrofit phoneme controllability onto a pretrained conversational TTS model without any pre/mid-training, using an ARPAbet vocabulary exten-sion, continued phoneme-augmented ...
| Authors | Yashish M. Siriwardena, Dinesh K. Gnanasekaran, Tanmay Laud et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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