Paper Citation Record · LEDGER

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement

As of 16 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2606.23332.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.23332 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T06:49:46.425849Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T06:49:46.425849Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-04T12:29:51.736855Z

Reference resolution

40 of 40 outbound references displayed

verified exact20
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d59e4e19-cede-434b-b783-f9f708388b92 · outbound

This paper cites A particularly challenging scenario arises when a far-field device, such as a table-top microphone, captures, enhances, and streams audio back to the user.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement A particularly challenging scenario arises when a far-field device, such as a table-top microphone, captures, enhances, and streams audio back to the user

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a783f39-8edd-43c0-82fa-a6e865b0d222 · outbound

This paper cites Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T12:29:51.738001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e0d50dd2-252e-4f80-98a2-2a52062bc284 · outbound

This paper cites base" and.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement base" and

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f2f715c-e44e-4a2c-b3bd-84aafc902889 · outbound

This paper cites When comparing task objectives, OVC and TSE appear comparably difficult (cf.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement When comparing task objectives, OVC and TSE appear comparably difficult (cf

Reference 4

Resolution: malformed identifier; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1f1b91d-28ec-4a5b-8dea-3e38bb0cf20c · outbound

This paper cites an unresolved cited work.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3f0e5ff-2140-4187-b11b-5fa24996c918 · outbound

This paper cites AI tools were used solely for grammar correction.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement AI tools were used solely for grammar correction

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56f45bbc-63b1-4d8a-9fdf-d1cceb1e93d4 · outbound

This paper cites Tolerable hearing aid delays. I. Estimation of limits imposed by the auditory path alone using simulated hearing losses,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Tolerable hearing aid delays. I. Estimation of limits imposed by the auditory path alone using simulated hearing losses,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4422109-7386-45e2-a7f3-37a84e1f2620 · outbound

This paper cites Disturbance caused by varying prop- agation delay in non-occluding hearing aid fittings,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Disturbance caused by varying prop- agation delay in non-occluding hearing aid fittings,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27ee5aa1-4d8f-41d2-9c59-1eff79e6e692 · outbound

This paper cites Tolerable hearing-aid delays: IV. Effects on subjective disturbance during speech production by hearing-impaired subjects,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Tolerable hearing-aid delays: IV. Effects on subjective disturbance during speech production by hearing-impaired subjects,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d375c5-a65f-47ab-a0c8-fef53147601e · outbound

This paper cites Separate and Re- construct: Asymmetric Encoder-Decoder for Speech Separation,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Separate and Re- construct: Asymmetric Encoder-Decoder for Speech Separation,

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.723870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a322941b-9a8d-4b1f-aea3-5e320c81eb26 · outbound

This paper cites SepMamba: State-space models for speaker separation using Mamba.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement SepMamba: State-space models for speaker separation using Mamba

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.694431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 47844663-ac23-4f91-b26b-d4e6c44ecd98 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.689432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b11b0929-031a-47a1-ae92-5bef3021ffc7 · outbound

This paper cites Were RNNs All We Needed?.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Were RNNs All We Needed?

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.730169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ea48bf71-a931-47e3-aff6-2242564c6740 · outbound

This paper cites TaSNet: Time-Domain Audio Separa- tion Network for Real-Time, Single-Channel Speech Separation,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement TaSNet: Time-Domain Audio Separa- tion Network for Real-Time, Single-Channel Speech Separation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4b6af01-2edd-4d16-b24e-c9f39a75f9e6 · outbound

This paper cites Conv-TasNet: Surpassing Ideal Time-Frequency Magni- tude Masking for Speech Separation,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Conv-TasNet: Surpassing Ideal Time-Frequency Magni- tude Masking for Speech Separation,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da60ea97-0bc3-4100-8d80-3755ba49ae7d · outbound

This paper cites Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.732783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9d2fbe29-2033-4c11-bf51-a2f59df3b007 · outbound

This paper cites TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and Enhancement

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.727744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 508f4333-4d87-4f56-b9c2-88e8bb82dda0 · outbound

This paper cites Tolerable hearing aid delays. II. Estimation of limits imposed during speech production,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Tolerable hearing aid delays. II. Estimation of limits imposed during speech production,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26df3047-7688-4e7f-933a-e0dc8b985954 · outbound

This paper cites Improving Speaker Discrimination of Target Speech Extraction With Time-Domain Speakerbeam,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Improving Speaker Discrimination of Target Speech Extraction With Time-Domain Speakerbeam,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8a45f7a-34ac-45af-9b3b-52dd354e00cb · outbound

This paper cites Listen only to me! How well can target speech extraction handle false alarms?.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Listen only to me! How well can target speech extraction handle false alarms?

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.691971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 691e8a3f-be64-49c5-9cfd-5c7cc6975800 · outbound

This paper cites TEA-PSE: Tencent-Ethereal-Audio-Lab Personal- ized Speech Enhancement System for ICASSP 2022 DNS Chal- lenge,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement TEA-PSE: Tencent-Ethereal-Audio-Lab Personal- ized Speech Enhancement System for ICASSP 2022 DNS Chal- lenge,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e8f8fff-1759-43d0-bb64-01bc5a8dd500 · outbound

This paper cites SpeakerBeam-SS: Real-time Target Speaker Extraction with Lightweight Conv-TasNet and State Space Modeling.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement SpeakerBeam-SS: Real-time Target Speaker Extraction with Lightweight Conv-TasNet and State Space Modeling

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.687116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e65eda6-2a84-499a-b235-3b7412fa0e45 · outbound

This paper cites Target Speech Extraction with Pre-trained Self-supervised Learning Models.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Target Speech Extraction with Pre-trained Self-supervised Learning Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.735445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d04d6f25-a4c7-47d9-a93e-853a43bee6cd · outbound

This paper cites Diagonal State Spaces are as Effective as Structured State Spaces.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Diagonal State Spaces are as Effective as Structured State Spaces

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.715827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 45c55e70-e716-4aaf-8bbf-5f60f0fb24b6 · outbound

This paper cites ICASSP 2023 Acoustic Echo Cancellation Challenge,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement ICASSP 2023 Acoustic Echo Cancellation Challenge,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bf34f55-d07a-4d25-a651-cd16b8ea2865 · outbound

This paper cites A Progressive Neural Network for Acoustic Echo Can- cellation,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement A Progressive Neural Network for Acoustic Echo Can- cellation,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba41bfed-70be-41cb-b5eb-323f68047c01 · outbound

This paper cites Lib- rispeech: An ASR corpus based on public domain audio books,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Lib- rispeech: An ASR corpus based on public domain audio books,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb2bf934-a8d2-4c0c-92a9-b4ba5f518611 · outbound

This paper cites WHAM!: Extending Speech Separation to Noisy Environments.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement WHAM!: Extending Speech Separation to Noisy Environments

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.720996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 65e970a6-19c2-4c65-a180-31bf8fa1ff0e · outbound

This paper cites LibriMix: An Open-Source Dataset for Generalizable Speech Separation.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.684420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 778e06b3-8ec5-4470-a932-6b3c308c8c1b · outbound

This paper cites Layer Normalization.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Layer Normalization

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.704339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 126164d3-5d6e-4693-b9d6-91e8aea3ae2a · outbound

This paper cites Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.713225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 908aaf08-db1a-4296-ad6a-1b56f4da9b4b · outbound

This paper cites Resurrecting Recurrent Neural Networks for Long Sequences.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Resurrecting Recurrent Neural Networks for Long Sequences

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.718429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 89324029-61f9-4566-9f1c-ed7f8ff3a6d1 · outbound

This paper cites Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.708436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 456435af-0c6c-45cd-93f7-60861058dfa4 · outbound

This paper cites Unsupervised Sound Separation Using Mixture Invariant Training,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Unsupervised Sound Separation Using Mixture Invariant Training,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1cb0da1-91c3-4b8f-8bf7-35be4ea44903 · outbound

This paper cites SDR - half-baked or well done?.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement SDR - half-baked or well done?

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.701944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb71144c-0b83-4897-9564-67f4e1a4a8ab · outbound

This paper cites Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.699304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3a3c191b-a47d-41f4-b2d8-4e0a2ff25346 · outbound

This paper cites Decoupled Weight Decay Regularization.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Decoupled Weight Decay Regularization

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:29:51.710799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b33aa230-b1e8-473a-93bc-14119fa94dc0 · outbound

This paper cites Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs,

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:29:51.696849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 62641c1a-b4eb-46d1-b00b-19642fdf0db5 · outbound

This paper cites PYIN: A fundamental frequency esti- mator using probabilistic threshold distributions,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement PYIN: A fundamental frequency esti- mator using probabilistic threshold distributions,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2757c44-ab5a-4322-a738-398421d74d9c · outbound

This paper cites YIN, a fundamental fre- quency estimator for speech and music,.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement YIN, a fundamental fre- quency estimator for speech and music,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-26T06:49:46.425849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6a783f39-8edd-43c0-82fa-a6e865b0d222 · inbound