arXiv (All)
open access
Measurement-Based Bitrate-Energy-Quality Analysis of Neural Audio Codec Decoders on Laptop and Phone Platforms
Neural audio codecs can achieve similar objective quality at lower bitrates than conventional codecs, but their decoder-side computational cost may offset this bitrate advantage on battery-powered client devices. This paper presents a measurement-based rate--energy--quality analysis of four neural a
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Decoupled Contrastive Decoding via Expert-Aligned Drafting#1013654
- EdgeVolution: democratizing multi-objective neural architecture search and end-to-end deployment on microcontrollers.#312461
- Confusion-Erasure Bounds of Error-Bounded Decoders under QAM#1070117
- Massively Parallel Reinforcement Learning with a Chaotic Reconfigurable Clockless Chip#1131189
- EchoLedger: A Tonal Responsibility Field for Nonlinear Utterance Resonance and Ethical Drift Preservation: Toward a Sovereign Echo-Based Ledger of Tension Amplitudes in the ToneVerse Moat Architecture#729494
Record · ID 1128790
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive