Communicating Sound Through Natural Language
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Abstract (arXiv)
Natural language is widely used to describe, prompt, and control audio systems, but rarely serves as the representation carrying audio itself. We introduce lexical acoustic coding (LAC), a framework in which pre-trained LLM sender and receiver agents transmit sound through natural language. Under fixed system prompts, the agents write their own analysis and synthesis code, communicating only through a lexical sentence, shared vocabulary, and optional symbolic music structure. The sender analyzes an input waveform into interpretable, non-learned acoustic descriptors, quantizes each with a feature-specific interval vocabulary, and verbalizes the lexical code as English. The receiver parses the sentence back into lexical-acoustic constraints and renders a waveform through closed-loop refinement. The transmitted text serves as both a rich caption and as the transport representation itself. We frame LAC as a finite-rate lossy quantizer, exposing trade-offs between vocabulary size, rate, and fidelity. Experiments on short sounds and symbolic music transfer show that plain text preserves measurable acoustic structure while remaining interpretable, editable, and native to LLM-mediated communication.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 18 of its 45 references that are in the map. First posted on arXiv 9 May 2026.
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References · 18
- 2021SoundStream: An End-to-End Neural Audio Codeccited by 771
- 2022High Fidelity Neural Audio Compressioncited by 687
- 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 616
- 2023MusicLM: Generating Music From Textcited by 448
- 2018Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Datasetcited by 217
- 2020DDSP: Differentiable Digital Signal Processingcited by 178
- 2024SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generationcited by 33
- 2021MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modelingcited by 32
- 2025TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modelingcited by 16
- 2025TaDiCodec: Text-aware Diffusion Speech Tokenizer for Speech Language Modelingcited by 13
- 2023Semantic Communications using Foundation Models: Design Approaches and Open Issuescited by 9
- 2026UniAudio 2.0: A Unified Audio Language Model with Text-Aligned Factorized Audio Tokenizationcited by 5
6 more
- 2025Robust Steganography from Large Language Modelscited by 4
- 2024SILA: Signal-to-Language Augmentation for Enhanced Control in Text-to-Audio Generationcited by 3
- 2025LLMs can hide text in other text of the same lengthcited by 2
- 2022Word Embeddings for Automatic Equalization in Audio Mixingcited by 1
- 2024L2· M = C2 Large Language Models are Covert Channelscited by 1
- 2026TADA: A Generative Framework for Speech Modeling via Text-Acoustic Dual Alignmentcited by 1
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- 2024SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Sound
- 2026Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions
- 2026FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation
- 2026Unified Synthesis of Compositional Speech and Sound from Free-Form Text Prompts
- 2025Discrete Audio Tokens: More Than a Survey!
- 2025Make Some Noise: Towards LLM audio reasoning and generation using sound tokens