arXiv Machine Learning
Aug 7
LILAC: An Idempotent Neural Speech Codec
arXiv:2608. 05727v1 Announce Type: cross Abstract: Neural Audio Codecs are widely adopted in speech generation and editing.
Probing Low Frame Rate Degradation in Neural Audio Codecs
arXiv:2606. 16969v1 Announce Type: cross Abstract: Low frame rates in neural audio codecs are attractive for autoregressive speech synthesis, where the generation cost scales linearly with the sequence length.
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arXiv AI
Aug 11
VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference
arXiv:2608. 08569v1 Announce Type: new Abstract: Recent advancements in Speech Large Language Models have demonstrated remarkable capabilities in understanding complex audio tasks.
arXiv AI
Jun 8
Benchmarking Language Modeling for Lossless Compression of Full-Fidelity Audio
arXiv:2603. 08683v2 Announce Type: replace-cross Abstract: Autoregressive "language" models (LMs) trained on raw waveforms can be repurposed for lossless audio compression, but prior work is limited to 8-bit audio, leaving open whether such approaches work for practical settings (16/24-bit) and can compete with existing codecs.
arXiv Machine Learning
Jun 29
Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding
arXiv:2606. 27320v1 Announce Type: cross Abstract: Neural audio autoencoders have become a core component of compression, feature extraction, and generation.
arXiv Machine Learning
Jul 10
Structural Bottlenecks on Frequency Representation in End-to-End Audio Models
arXiv:2607. 08545v1 Announce Type: cross Abstract: End-to-end neural audio models achieve high-fidelity compression and generation.
arXiv AI
Jul 1
BEST-RQ-2: Contextualize-Then-Predict, a Two-Step Approach for Self-Supervised Audio Representations
arXiv:2606. 30700v1 Announce Type: cross Abstract: Self-supervised learning enables audio representations that transfer across domains and tasks.
arXiv AI
Jul 28
The Equalizer: Introducing Shape-Gain Decomposition in Neural Audio Codecs
arXiv:2602. 15491v2 Announce Type: replace-cross Abstract: Neural audio codecs (NACs) typically encode the short-term energy (gain) and normalized structure (shape) of speech/audio signals jointly within the same latent space.
arXiv Machine Learning
Jul 24
Encode Once, Decode Never: Reusing Audio LM Internals for Efficient Temporal Localization
arXiv:2602. 10230v2 Announce Type: replace Abstract: Audio language models process input audio into rich frame-level representations, but the standard approach to temporal localization generates timestamps as sequences of text tokens, which discards the frame-level representations in favor of autoregressive decoding.
Hugging Face Trending Papers
Jun 3
CleanCodec: Efficient and Robust Speech Tokenization via Perceptually Guided Encoding
Neural audio codecs are a key component of speech processing pipelines, compressing audio into discrete tokens for downstream modeling. However, existing codecs struggle to balance reconstruction quality with token efficiency, often encoding perceptually irrelevant information such as background noise and recording artifacts at the expense of linguistically and acoustically meaningful content.
arXiv AI
Jun 19
FlowFake: Liquid Networks for Audio Deepfake Detection
arXiv:2606. 19579v1 Announce Type: cross Abstract: Audio deepfakes generated by neural text-to-speech and voice-cloning systems threaten speaker verification and public discourse at scale.
arXiv AI
Jul 3
An Efficient vLLM-Based Inference Pipeline for Unified Audio Understanding and Generation
arXiv:2607. 02119v1 Announce Type: cross Abstract: While Large Multimodal Models excel in comprehension, high-throughput inference engines lack native support for multimodal generation.
arXiv AI
Jul 14
VoxENES 2026: Benchmarking Generalization of Speech Spoofing Detectors Against LLM-Era TTS and Voice Conversion
arXiv:2607. 11706v1 Announce Type: cross Abstract: Modern LLM-driven text-to-speech (TTS) and voice conversion (VC) systems produce synthetic speech that differs from the generators represented in many legacy spoofing benchmarks.