Bridging the Gap: Converting Read Text to Conversational Dialogue
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Computer Science > Computation and Language
arXiv:2605.18001 (cs)
[Submitted on 18 May 2026]
Title:Bridging the Gap: Converting Read Text to Conversational Dialogue
Authors:Parshav Singla, Agnik Banerjee, Aaditya Arora, Shruti Aggarwal, Anil Kumar Verma, Vikram C M, Raj Prakash Gohil, Gopal Kumar Agarwal
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Abstract:In recent advancements within speech processing, converting read speech to conversational speech has gained significant attention. The primary challenge in this domain is maintaining naturalness and intelligibility while minimizing computational overhead for real-time applications. Traditional read speech often lacks the nuanced prosodic variation essential for natural conversational interactions, posing challenges for applications in virtual assistants, customer service, and language learning tools. This paper introduces a novel approach, Prosodic Adjustment with Conversational Context (PACC), aimed at converting read speech into natural conversational speech used in various modern applications. PACC utilizes advanced deep neural networks to analyze and modify prosodic features such as intonation, stress, and rhythm. Unlike conventional methods, our approach uses High-Fidelity Generative Adversarial Networks (HiFi-GAN) for speech synthesis. Our experimental results demonstrate significant improvements in speech conversion, enhancing naturalness and achieving better model accuracy with additional training on speech datasets. This research establishes new benchmarks in speech conversion tasks and Mean Opinion Score (MOS) evaluation for testing model accuracy, and we show that our approach can be successfully extended to other speech conversion applications.
| Comments: | 11 pages, 4 figures. Published in ICICC 2025, Springer Lecture Notes in Networks and Systems |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.18001 [cs.CL] |
| (or arXiv:2605.18001v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.18001
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | Innovative Computing and Communications (ICICC 2025), Lecture Notes in Networks and Systems, Springer Nature, 2025, pp. 543-556 |
| Related DOI: | https://doi.org/10.1007/978-981-96-6681-2_38
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