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HASCom: A Heterogeneous Affective-Semantic Communication Framework for Speech Transmission.

Zhenjia Yu1, Taojie Zhu2, Md Arman Hossain3

  • 1Portland Institute, Nanjing University of Posts and Telecommunications, Nanjing 220003, China.

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Summary
This summary is machine-generated.

This study introduces a novel speech communication framework (HASCom) for transmitting both linguistic meaning and emotional tone over wireless networks. HASCom enhances natural human interactions by preserving affective information, outperforming existing methods.

Keywords:
diffusion modelemotional speechheterogeneous transmissionlowercase communication

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Area of Science:

  • Wireless Communication
  • Speech Processing
  • Affective Computing

Background:

  • Next-generation wireless networks demand richer communication beyond text.
  • Current speech frameworks prioritize semantic accuracy, ignoring crucial affective cues like emotion and tone.
  • Natural human interaction relies heavily on conveying and understanding affective information.

Purpose of the Study:

  • To propose the Heterogeneous Affective Speech Semantic Communication (HASCom) framework for robust speech transmission over wireless channels.
  • To enable the accurate transmission of both linguistic content and affective (emotional) information in speech.
  • To improve the naturalness and expressiveness of speech communication in digital systems.

Main Methods:

  • Designed a heterogeneous dual-stream architecture separating phoneme-level semantics and emotional embeddings.
  • Employed Low-Density Parity-Check (LDPC) coding for reliable discrete semantic transmission.
  • Utilized Deep Joint Source-Channel Coding (JSCC) for continuous emotional feature transmission.
  • Developed a prior-guided diffusion reconstruction module for enhanced speech recovery at the receiver.

Main Results:

  • HASCom significantly outperforms state-of-the-art baselines in speech semantic communication.
  • Achieved superior objective semantic similarity and subjective Mean Opinion Score (MOS) at low Signal-to-Noise Ratios (SNRs).
  • JSCC modules demonstrated ultra-low inference latency (<0.1 ms), confirming high efficiency.

Conclusions:

  • The HASCom framework offers a robust and efficient solution for transmitting expressive speech, including affective information.
  • HASCom enhances human-centric communication in wireless systems by preserving emotional nuances.
  • The proposed methods show significant potential for practical deployment in advanced communication systems.