ARXIV:2605.30965 · TEXT-TO-SPEECH · SUBMITTED 01 JUN · 20:23 UTC · FRESHNESS STALE

VerifiedSource: PDF linkedVerifiedPaperPack: citation fields availablePartialProof: unverified proof status

ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment

Jun-Hak Yun · Seung-Bin Kim · Seong-Whan Lee · arXiv

ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

Ship in 2-4 weeks›Score7.0Evidence unverified

Opportunity summary

Pain ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

Evidence 0 refs | 4 sources | 67% coverage

Blocker Evidence unverified

Open Build Read PDF Signal Canvas Track

PROBLEM

ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment. However, jointly generating speech with environmental audio remains challenging due to the inherent…

METHOD

Full abstract

Recent advancements in text-guided audio generation have yielded promising results in diverse domains, including sound effects, speech, and music. However, jointly generating speech with environmental audio remains challenging due to the inherent disparities in their acoustic patterns and temporal dynamics. We propose ImmersiveTTS, an environment-aware text-to-speech (TTS) model that generates natural speech seamlessly integrated within environmental contexts by explicitly modeling cross-modal interactions. Our model builds on a multimodal diffusion transformer and fuses transcript-aligned speech latent with text-conditioned environmental context via joint attention. To enhance semantic consistency, we introduce a domain-specific representation alignment objective tailored to environment-aware TTS, leveraging complementary self-supervised representations from speech and audio encoders. Experimental results show that ImmersiveTTS achieves higher naturalness, intelligibility, and audio fidelity than existing approaches across objective metrics and human listening tests.

RESULT

ScienceToStartup currently rates this 7.0/10 on the public viability pass. Recent advancements in text-guided audio generation have yielded promising results in diverse domains, including sound effects, speech, and music. A public repository is linked,…

WHY NOW

Text-to-Speech moved forward this cycle; last verified June 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.

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Opportunity summary

Score7.0

PainImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

Evidence0 refs | 4 sources | 67% coverage

Blockerno shell-level blocker reported

Analysis summary

ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

VerifiedSource: PDF linkedVerifiedPaperPack: citation fields availablePartialProof: unverified proof status

Competitive landscape

ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

Segment

Text-to-Speech

Adoption evidence

Public code linked for build inspection

Commercial read

7.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

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Competitive landscape

ImmersiveTTS is an environment-aware text-to-speech model that seamlessly integrates speech with environmental audio using a multimodal diffusion transformer and domain-specific alignment.

Segment

Text-to-Speech

Adoption evidence

Public code linked for build inspection

Commercial read

7.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment

ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment

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