FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates
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Abstract (arXiv)
Neural audio codecs are foundational to speech language models. It is expected to have a low frame rate and decoupled semantic and acoustic information. A lower frame rate codec can reduce the computational cost of speech language models by shortening the sequence length. Recent studies have developed 12.5Hz low-frame-rate audio codecs, but even lower frame rate codecs remain underexplored. We find that a major challenge for very low frame rate tokens is missing semantic information. This paper introduces FlexiCodec to address this limitation. FlexiCodec improves semantic preservation with a dynamic frame rate approach and introduces a novel architecture featuring an ASR feature-assisted dual stream encoding and Transformer bottlenecks. With dynamic frame rates, it uses less frames at information-sparse regions through adaptively merging semantically similar frames. A dynamic frame rate also allows FlexiCodec to support inference-time controllable frame rates between 3Hz and 12.5Hz. Experiments on 6.25Hz, 8.3Hz and 12.5Hz average frame rates confirm that FlexiCodec excels over baseline systems in semantic information preservation and delivers a high audio reconstruction quality. We also validate the effectiveness of FlexiCodec in language model-based TTS. Demos are available at: https://flexicodec.github.io. Code is available at: https://github.com/amphionteam/flexicodec.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Oct 2025.
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Citing papers per year: 2026: 10.
10 papers.
- 2026Beyond Fixed Frames: Dynamic Character-Aligned Speech Tokenizationcited by 4
- 2026Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codeccited by 2
- 2026DeepASMR: LLM-Based Zero-Shot ASMR Speech Generation for Anyone of Any Voicecited by 1
- 2026Probing Low Frame Rate Degradation in Neural Audio Codecscited by 0
- 2026Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Codingcited by 0
- 2026ZipCodec: Ultra-Low-Frame-Rate Streaming Speech Codingcited by 0
- 2026TokenMapper: A Step Toward Interoperable Speech Token Translationcited by 0
- 2026LACE: Layer-Wise Compression for Dynamic Frame Rate Codecscited by 0
- 2026Q-SPT: Learnable Query-Based Compression for Low-Frame-Rate Speech Tokenizationcited by 0
- 2026GS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Codingcited by 0
- 2026GS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Coding3 Oct 2026
- 2026Q-SPT: Learnable Query-Based Compression for Low-Frame-Rate Speech Tokenization1 Oct 2026
- 2026LACE: Layer-Wise Compression for Dynamic Frame Rate Codecs15 Sep 2026
- 2026TokenMapper: A Step Toward Interoperable Speech Token Translation11 Sep 2026
- 2026ZipCodec: Ultra-Low-Frame-Rate Streaming Speech Coding10 Sep 2026
- 2026Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding25 Jun 2026
- 2026Probing Low Frame Rate Degradation in Neural Audio Codecs15 Jun 2026
- 2026Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codec6 Mar 2026
- 2026Beyond Fixed Frames: Dynamic Character-Aligned Speech Tokenization30 Jan 2026
- 2026DeepASMR: LLM-Based Zero-Shot ASMR Speech Generation for Anyone of Any Voice22 Jan 2026