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20192026
most citedAudio Editing with Non-Rigid Text Prompts

5 citations · 11 across the 12 of their papers we have counts for

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8 papers · 1 filter

cs.SD2026

ZipCodec: Ultra-Low-Frame-Rate Streaming Speech Coding

Luca Della Libera, Cem Subakan, Mirco Ravanelli

Neural audio codecs are a fundamental component of modern speech generation systems. While recent codecs achieve increasingly low bitrates, reducing frame rate remains challenging,…

cs.SD2026

Exploring Token-Space Manipulation in Latent Audio Tokenizers

Francesco Paissan, Luca Della Libera, Mirco Ravanelli +1

Neural audio codecs provide compact discrete representations for speech generation and manipulation. However, most codecs organize tokens as frame-level sequences, making it diffic…

cs.SD2026

LL-SDR: Low-Latency Speech enhancement through Discrete Representations

Jingyi Li, Luca Della Libera, Mirco Ravanelli +2

Many speech enhancement (SE) methods rely on continuous representations. Recently, discrete audio tokens have been explored to enable autoregressive generation for SE. However, it…

cs.SD2024

How Should We Extract Discrete Audio Tokens from Self-Supervised Models?

Pooneh Mousavi, Jarod Duret, Salah Zaiem +4

Discrete audio tokens have recently gained attention for their potential to bridge the gap between audio and language processing. Ideal audio tokens must preserve content, paraling…

cs.SD2024★ 1 cited

DASB - Discrete Audio and Speech Benchmark

Pooneh Mousavi, Jarod Duret, Darius Petermann +5

Discrete audio tokens have recently gained considerable attention for their potential to bridge audio and language processing, enabling multimodal language models that can both gen…

cs.SD2024★ 1 cited

Listenable Maps for Zero-Shot Audio Classifiers

Francesco Paissan, Luca Della Libera, Mirco Ravanelli +1

Interpreting the decisions of deep learning models, including audio classifiers, is crucial for ensuring the transparency and trustworthiness of this technology. In this paper, we…

cs.SD2024

Focal Modulation Networks for Interpretable Sound Classification

Luca Della Libera, Cem Subakan, Mirco Ravanelli

The increasing success of deep neural networks has raised concerns about their inherent black-box nature, posing challenges related to interpretability and trust. While there has b…

cs.SD2023★ 5 cited

Audio Editing with Non-Rigid Text Prompts

Francesco Paissan, Luca Della Libera, Zhepei Wang +3

In this paper, we explore audio-editing with non-rigid text edits. We show that the proposed editing pipeline is able to create audio edits that remain faithful to the input audio.…