Speech Extraction

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (48 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline
  25 May 2025 1 repository listed
  On the other hand, generative models for TSE lag in perceptual quality and intelligibility.
• Beyond Speaker Identity: Text Guided Target Speech Extraction
  15 Jan 2025 1 repository listed
  To train and evaluate our model, we introduce a new dataset TextrolMix with speech mixtures and natural language descriptions.
• Generative Speech Foundation Model Pretraining for High-Quality Speech Extraction and Restoration
  24 Sep 2024 1 repository listed
  The proposed method is evaluated on multiple speech restoration tasks, including speech denoising, bandwidth extension, codec artifact removal, and target speaker extraction.
• Look Once to Hear: Target Speech Hearing with Noisy Examples
  10 May 2024 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  We present the first enrollment interface where the wearer looks at the target speaker for a few seconds to capture a single, short, highly noisy, binaural example of the target speaker.
• Neural Target Speech Extraction: An Overview
  31 Jan 2023 1 repository listed
  Humans can listen to a target speaker even in challenging acoustic conditions that have noise, reverberation, and interfering speakers.
• Analysis of impact of emotions on target speech extraction and speech separation
  15 Aug 2022 1 repository listed
  One of the factors causing such degradation may be intrinsic speaker variability, such as emotions, occurring commonly in realistic speech.
• On the Role of Spatial, Spectral, and Temporal Processing for DNN-based Non-linear Multi-channel Speech Enhancement
  22 Jun 2022 1 repository listed
  Employing deep neural networks (DNNs) to directly learn filters for multi-channel speech enhancement has potentially two key advantages over a traditional approach combining a linear spatial filter with an independent…
• DPCCN: Densely-Connected Pyramid Complex Convolutional Network for Robust Speech Separation And Extraction
  27 Dec 2021 1 repository listed
  Particularly, we find that the Mixture-Remix fine-tuning with DPCCN significantly outperforms the TD-SpeakerBeam for unsupervised cross-domain TSE, with around 3.
• Target Speech Extraction Based on Blind Source Separation and X-vector-based Speaker Selection Trained with Data Augmentation
  16 May 2020 1 repository listed
  Extracting the desired speech from a mixture is a meaningful and challenging task.
• Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
  23 Jan 2020 1 repository listed
  First, we propose a time-domain implementation of SpeakerBeam similar to that proposed for a time-domain audio separation network (TasNet), which has achieved state-of-the-art performance for speech separation.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.