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Paper Citation Record · LEDGER

Technical Report for MERL's Real-TSE Challenge Submission

As of 22 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.09043.

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

pith.paper-citation-record.v1
2607.09043 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T00:46:07.473150Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 45de677f-dd71-40c4-8ab4-6bc719a5a567 · outbound

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

Technical Report for MERL's Real-TSE Challenge Submission LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Reference 1

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source=pdf_text observed=2026-07-13T00:46:07.473150Z digest=sha256:8b54b2705cfc13b266302d0da6d3b844cc4336e2983dcf7f45946d9e96253d97

Observation 668bc8f3-49e6-4558-87b1-75bf628efd60 · outbound

This paper cites CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings,.

Technical Report for MERL's Real-TSE Challenge Submission CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings,

Reference 2

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Observation 9fb26037-5de1-48d8-a3e4-b083dbfbc968 · outbound

This paper cites DiPCo – dinner party corpus,.

Technical Report for MERL's Real-TSE Challenge Submission DiPCo – dinner party corpus,

Reference 3

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Observation 9cafb775-b84e-439a-9050-28a2717c0306 · outbound

This paper cites REAL-T: Real conversational mixtures for target speaker extraction,.

Technical Report for MERL's Real-TSE Challenge Submission REAL-T: Real conversational mixtures for target speaker extraction,

Reference 4

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Observation 46b270a8-e1b0-4b1b-8378-30cdd1ce11a8 · outbound

This paper cites Multi-level speaker representation for target speaker extraction,.

Technical Report for MERL's Real-TSE Challenge Submission Multi-level speaker representation for target speaker extraction,

Reference 5

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Observation 53a2da5e-fbaf-4f03-a4ef-be7c2ed6ed8f · outbound

This paper cites ECAPA-TDNN: Emphasized channel attention, propagation and aggregation in TDNN based speaker verification,.

Technical Report for MERL's Real-TSE Challenge Submission ECAPA-TDNN: Emphasized channel attention, propagation and aggregation in TDNN based speaker verification,

Reference 6

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Observation 4f629c90-bc05-4e5d-8a1c-b62ab48e169d · outbound

This paper cites LibriSpeech: An ASR corpus based on public domain audio books,.

Technical Report for MERL's Real-TSE Challenge Submission LibriSpeech: An ASR corpus based on public domain audio books,

Reference 7

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Observation 0f856eea-f753-4d19-8858-491171590f15 · outbound

This paper cites V oxCeleb2: Deep speaker recognition,.

Technical Report for MERL's Real-TSE Challenge Submission V oxCeleb2: Deep speaker recognition,

Reference 8

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Observation 26d14a16-ccc4-4176-853d-6fd028f1959d · outbound

This paper cites Emilia: A large- scale, extensive, multilingual, and diverse dataset for speech generation,.

Technical Report for MERL's Real-TSE Challenge Submission Emilia: A large- scale, extensive, multilingual, and diverse dataset for speech generation,

Reference 9

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source=pdf_text observed=2026-07-13T00:46:07.473150Z digest=sha256:4999da8daa09a411871428d755e4903b06c8a9442612f0d99d1019d86f8e55c7

Observation e8c66616-16d3-48d1-8bcc-821371d9af4c · outbound

This paper cites CSTR VCTK Corpus: English multi-speaker corpus for CSTR voice cloning toolkit (version 0.92),.

Technical Report for MERL's Real-TSE Challenge Submission CSTR VCTK Corpus: English multi-speaker corpus for CSTR voice cloning toolkit (version 0.92),

Reference 10

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Observation 8efdac70-2656-40b4-97d2-b18a92b2fea1 · outbound

This paper cites EARS: An anechoic fullband speech dataset benchmarked for speech enhancement and dereverberation,.

Technical Report for MERL's Real-TSE Challenge Submission EARS: An anechoic fullband speech dataset benchmarked for speech enhancement and dereverberation,

Reference 11

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Observation edf4b75b-03df-4d9c-b44e-adfe70774a54 · outbound

This paper cites ClearerV oice-Studio: Bridging advanced speech processing research and practical deployment,.

Technical Report for MERL's Real-TSE Challenge Submission ClearerV oice-Studio: Bridging advanced speech processing research and practical deployment,

Reference 12

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Observation 6547b1f9-7046-4481-b76a-7d6d386e02d9 · outbound

This paper cites MossFormer: Pushing the performance limit of monaural speech separation using gated single-head transformer with convolution-augmented joint self-attentions,.

Technical Report for MERL's Real-TSE Challenge Submission MossFormer: Pushing the performance limit of monaural speech separation using gated single-head transformer with convolution-augmented joint self-attentions,

Reference 13

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source=pdf_text observed=2026-07-13T00:46:07.473150Z digest=sha256:721688ccc1d4b0e6558dc2d335fc01da94ca4f88b33ce572223664635639d6bf

Observation ebd377a1-a72b-48eb-99f0-ff4b4f83001f · outbound

This paper cites WeSpeaker: A research and production oriented speaker embedding learning toolkit,.

Technical Report for MERL's Real-TSE Challenge Submission WeSpeaker: A research and production oriented speaker embedding learning toolkit,

Reference 14

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Observation b906c1af-a526-4703-85b7-2023a222cb54 · outbound

This paper cites Montreal forced aligner: Trainable text-speech alignment using Kaldi,.

Technical Report for MERL's Real-TSE Challenge Submission Montreal forced aligner: Trainable text-speech alignment using Kaldi,

Reference 15

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Observation aad424cb-ce15-4a18-bf28-b99005a720d4 · outbound

This paper cites ICASSP 2022 deep noise suppression challenge,.

Technical Report for MERL's Real-TSE Challenge Submission ICASSP 2022 deep noise suppression challenge,

Reference 16

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Observation 49930dd8-35cc-4fbb-bcd5-ce4ee8d8985a · outbound

This paper cites Pyroomacoustics: A python package for audio room simulation and array processing algorithms,.

Technical Report for MERL's Real-TSE Challenge Submission Pyroomacoustics: A python package for audio room simulation and array processing algorithms,

Reference 17

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Observation 2a873a62-bf88-498e-a960-aef57599ef82 · outbound

This paper cites The third CHiME speech separation and recognition challenge: Dataset, task and base- lines,.

Technical Report for MERL's Real-TSE Challenge Submission The third CHiME speech separation and recognition challenge: Dataset, task and base- lines,

Reference 18

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Observation b37269b7-5a37-42bb-b8d3-1f17dc0d0571 · outbound

This paper cites The diverse environments multi- channel acoustic noise database (DEMAND): A database of multichan- nel environmental noise recordings,.

Technical Report for MERL's Real-TSE Challenge Submission The diverse environments multi- channel acoustic noise database (DEMAND): A database of multichan- nel environmental noise recordings,

Reference 19

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Observation 2f11c419-bc0c-4a29-81fe-1a1831bdfdd1 · outbound

This paper cites FMA: A dataset for music analysis,.

Technical Report for MERL's Real-TSE Challenge Submission FMA: A dataset for music analysis,

Reference 20

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Observation 93ab1202-82b7-4922-a10a-4da6f5249ef8 · outbound

This paper cites FSD50K: An open dataset of human-labeled sound events,.

Technical Report for MERL's Real-TSE Challenge Submission FSD50K: An open dataset of human-labeled sound events,

Reference 21

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source=pdf_text observed=2026-07-13T00:46:07.473150Z digest=sha256:868db23c9c62e908edecfead10661281786141690c996b08b1fc8f1391886c27

Observation 82dcd745-3b1f-461e-a83d-f20d48cf7352 · outbound

This paper cites MUSAN: A Music, Speech, and Noise Corpus.

Technical Report for MERL's Real-TSE Challenge Submission MUSAN: A Music, Speech, and Noise Corpus

Reference 22

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source=pdf_text observed=2026-07-13T00:46:07.473150Z digest=sha256:9ef27b88c02fb2eac1ac93fa44377ab1775d43742ffb1f97b46ab16d2323956b

Observation c53e33f2-3f84-4f4a-8854-17d7b5b51aa3 · outbound

This paper cites WHAM!: Extending speech separation to noisy environments,.

Technical Report for MERL's Real-TSE Challenge Submission WHAM!: Extending speech separation to noisy environments,

Reference 23

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Observation 723cf22c-f13b-49e1-9a06-190c057497e4 · outbound

This paper cites URGENT challenge: Universality, robustness, and generalizability for speech en- hancement,.

Technical Report for MERL's Real-TSE Challenge Submission URGENT challenge: Universality, robustness, and generalizability for speech en- hancement,

Reference 24

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Observation b7e1005a-d13d-4b30-b8c9-5c7205714d87 · outbound

This paper cites The AMI meeting corpus: A pre-announcement,.

Technical Report for MERL's Real-TSE Challenge Submission The AMI meeting corpus: A pre-announcement,

Reference 25

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Observation dadd1aa8-abb5-4279-98e2-4eec2928f85f · outbound

This paper cites AISHELL-4: An open source dataset for speech enhancement, separation, recognition and speaker diarization in conference scenario,.

Technical Report for MERL's Real-TSE Challenge Submission AISHELL-4: An open source dataset for speech enhancement, separation, recognition and speaker diarization in conference scenario,

Reference 26

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Observation ba5a1f38-f383-41c5-8afe-837b86f73594 · outbound

This paper cites AISHELL-5: The first open-source in-car multi-channel multi-speaker speech dataset for automatic speech diarization and recognition,.

Technical Report for MERL's Real-TSE Challenge Submission AISHELL-5: The first open-source in-car multi-channel multi-speaker speech dataset for automatic speech diarization and recognition,

Reference 27

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Observation 4e70fe3c-dff9-4c4e-8f11-3ffddb176fd6 · outbound

This paper cites Front-end processing for the CHiME-5 dinner party scenario,.

Technical Report for MERL's Real-TSE Challenge Submission Front-end processing for the CHiME-5 dinner party scenario,

Reference 28

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Observation 75a22edc-90d0-4b13-9650-729ddd5edb97 · outbound

This paper cites Gen- erating training targets for real-world speech enhancement via close- to-distant microphone projection,.

Technical Report for MERL's Real-TSE Challenge Submission Gen- erating training targets for real-world speech enhancement via close- to-distant microphone projection,

Reference 29

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Observation 36d59202-b832-4f64-825e-a6ce4319009c · outbound

This paper cites Canary-1B-V2 & Parakeet- TDT-0.6B-V3: Efficient and high-performance models for multilingual ASR and AST,.

Technical Report for MERL's Real-TSE Challenge Submission Canary-1B-V2 & Parakeet- TDT-0.6B-V3: Efficient and high-performance models for multilingual ASR and AST,

Reference 30

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Observation 1c930929-9bbb-430b-aa8a-4f1fa7511566 · outbound

This paper cites Curriculum learning,.

Technical Report for MERL's Real-TSE Challenge Submission Curriculum learning,

Reference 31

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Observation 3abfbe33-957b-4927-991a-98aa17a3c69d · outbound

This paper cites Mind the Gap: Impact of Synthetic Conversational Data on Multi-Talker ASR and Speaker Diarization.

Technical Report for MERL's Real-TSE Challenge Submission Mind the Gap: Impact of Synthetic Conversational Data on Multi-Talker ASR and Speaker Diarization

Reference 32

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Observation cb4f4ad5-b2e0-4581-901a-a1cf75e88ed7 · outbound

This paper cites Decoupled weight decay regularization,.

Technical Report for MERL's Real-TSE Challenge Submission Decoupled weight decay regularization,

Reference 33

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Observation 2bc77aa6-f45e-408c-886e-5c42411f2b26 · outbound

This paper cites SGDR: Stochastic gradient descent with warm restarts,.

Technical Report for MERL's Real-TSE Challenge Submission SGDR: Stochastic gradient descent with warm restarts,

Reference 34

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Observation 2016e4be-6226-4bff-ad45-286c9cb37749 · outbound

This paper cites The text-to-speech in the wild (TITW) database,.

Technical Report for MERL's Real-TSE Challenge Submission The text-to-speech in the wild (TITW) database,

Reference 35

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Observation 0159c16d-3bc6-46ab-8cb1-cf44a881a700 · outbound

This paper cites Multilayer feedforward networks are universal approximators,.

Technical Report for MERL's Real-TSE Challenge Submission Multilayer feedforward networks are universal approximators,

Reference 36

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Observation bdd45ca2-5143-4737-94f8-63b91b0769ea · outbound

This paper cites Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition.

Technical Report for MERL's Real-TSE Challenge Submission Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition

Reference 37

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This paper cites Attacking UTMOS: Probing the Robustness of a Speech Quality Assessment Model.

Technical Report for MERL's Real-TSE Challenge Submission Attacking UTMOS: Probing the Robustness of a Speech Quality Assessment Model

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