When Fine-Tuning Fails and when it Generalises: Role of Data Diversity and Mixed Training in LLM-based TTS | ScienceToStartup | ScienceToStartup

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References (15)

[1]

FOCAL: A Novel Benchmarking Technique for Multi-modal Agents

2026Aditya Choudhary, Anupam Purwar

[2]

i-LAVA: Insights on Low Latency Voice-2-Voice Architecture for Agents

2025Anupam Purwar, Aditya Choudhary

[3]

UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech

Founder's Pitch

"Improving voice cloning in TTS systems through effective LoRA fine-tuning of LLMs."

Text-to-Speech•Score: 4•View PDF ↗

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When Fine-Tuning Fails and when it Generalises: Role of Data Diversity and Mixed Training in LLM-based TTS

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References (15)

Founder's Pitch

"Improving voice cloning in TTS systems through effective LoRA fine-tuning of LLMs."

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When Fine-Tuning Fails and when it Generalises: Role of Data Diversity and Mixed Training in LLM-based TTS

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References (15)

Founder's Pitch

"Improving voice cloning in TTS systems through effective LoRA fine-tuning of LLMs."

Commercial Viability Breakdown

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