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Paper Citation Record · LEDGER

Multiple Choice Learning for Efficient Speech Separation with Many Speakers

As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2411.18497.

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

pith.paper-citation-record.v1
2411.18497 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:12:18.083831Z

measured 39 of 39 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 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

39 of 39 outbound references displayed

  • verified exact3
  • verified fuzzy26
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38fda7ad-19d4-4639-8193-ff8b811a1f4e · outbound

This paper cites Automatic speech recognition in cocktail-party situations: A specific training for separated speech,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Automatic speech recognition in cocktail-party situations: A specific training for separated speech,

Reference 1

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raw_fallback, observed 2026-08-12T11:12:18.704556Z

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.

source=pdf_text observed=2026-08-12T11:12:17.948669Z digest=sha256:716cd58c9ae16f88cf03fa3c8585d9986b145706704bc40cdcd8b34f0f7e839c

Observation 51858476-056c-4b51-bdf7-16c01e7d2a00 · outbound

This paper cites Espnet-se: End- to-end speech enhancement and separation toolkit designed for asr integration,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Espnet-se: End- to-end speech enhancement and separation toolkit designed for asr integration,

Reference 2

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raw_fallback, observed 2026-08-12T11:12:18.693559Z

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.

source=pdf_text observed=2026-08-12T11:12:17.952938Z digest=sha256:46bbe07cdd8c9d73fb904d300cbe20f38fd3382085753373a0f71a666e046173

Observation 310eac9c-04b5-403b-9abb-1d41e41bc6f0 · outbound

This paper cites All-neural online source separation, counting, and diarization for meeting analysis,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers All-neural online source separation, counting, and diarization for meeting analysis,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.682636Z

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.

source=pdf_text observed=2026-08-12T11:12:17.956441Z digest=sha256:f67ec3f4aa00c21d296b2e71d0c768b0f9bf7b066653da646fe230f8bf4ebfe5

Observation 4e4b6418-2341-49f0-98c8-e625825025f1 · outbound

This paper cites Ts-sep: Joint diarization and separation conditioned on estimated speaker embeddings,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Ts-sep: Joint diarization and separation conditioned on estimated speaker embeddings,

Reference 4

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raw_fallback, observed 2026-08-12T11:12:18.671464Z

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.

source=pdf_text observed=2026-08-12T11:12:17.960076Z digest=sha256:0ec0d8dbd492dacfaecb460e56713ff5797ca9e844be462e505516e98bfdbc6a

Observation 41ede17a-2608-4abc-b90d-59308bcafd5a · outbound

This paper cites Singing-voice separation from monaural recordings using robust prin- cipal component analysis,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Singing-voice separation from monaural recordings using robust prin- cipal component analysis,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.660447Z

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.

source=pdf_text observed=2026-08-12T11:12:17.963380Z digest=sha256:30b962bd984a6421210cb0a4ce1cc1b3786ebb01af0b6dc052ca9b927db36ae7

Observation 0f11207c-cf74-4fda-bace-e6975ab348e5 · outbound

This paper cites Speech recognition by bilateral cochlear implant users in a cocktail- party setting,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Speech recognition by bilateral cochlear implant users in a cocktail- party setting,

Reference 6

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raw_fallback, observed 2026-08-12T11:12:18.648195Z

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.

source=pdf_text observed=2026-08-12T11:12:17.967791Z digest=sha256:4713dccf65f88c692d6bfc8c3d3ba6f489721fe6e41c201d98b4aca3f083842a

Observation f1a17075-3c58-431f-a3ea-18e401a3350c · outbound

This paper cites The cocktail party robot: Sound source separation and localisation with an active binaural head,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers The cocktail party robot: Sound source separation and localisation with an active binaural head,

Reference 7

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raw_fallback, observed 2026-08-12T11:12:18.636616Z

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.

source=pdf_text observed=2026-08-12T11:12:17.971982Z digest=sha256:e7e62fab3091f2eb488ebc48983716670e159af8d47f0e159cebd5abd40dd978

Observation fd2040c3-4ee0-4704-8cf3-e0c6204efd03 · outbound

This paper cites End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:17.975216Z digest=sha256:3edcb693c925923489da790da56bc2b7f4109b7d3fd31dc2ac602e387cbd0b11

Observation a24905a6-7503-42c7-bc62-5ba71a0326e6 · outbound

This paper cites Boosting unknown-number speaker separation with transformer decoder-based attractor,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Boosting unknown-number speaker separation with transformer decoder-based attractor,

Reference 9

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raw_fallback, observed 2026-08-12T11:12:18.625759Z

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.

source=pdf_text observed=2026-08-12T11:12:17.979538Z digest=sha256:e8bc954f58bfd2968ba3a56e455211f37638da5273957b68b603f55c0ff80d81

Observation 05e5e8e6-48fd-4fcc-945a-ebc42d4e4440 · outbound

This paper cites Looking to listen at the cocktail party: a speaker-independent audio-visual model for speech separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Looking to listen at the cocktail party: a speaker-independent audio-visual model for speech separation,

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:17.982608Z digest=sha256:3e192219e36273247d73a2f8b6106cf221c456142bec40fae777968d9cd87831

Observation 81cc6300-aed0-43e7-aa4c-2e32e5de74e0 · outbound

This paper cites SepIt: Approaching a Single Channel Speech Separation Bound.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers SepIt: Approaching a Single Channel Speech Separation Bound

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:17.985998Z digest=sha256:8dbd0e876a546c4291c38978cf2cd47f85b0762b6a75e09828dee13f6ef177c9

Observation 401310ac-70cc-4594-b6d8-362ea8b58460 · outbound

This paper cites Supervised speech separation based on deep learning: An overview,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Supervised speech separation based on deep learning: An overview,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:17.989908Z digest=sha256:320a8b2e17d935a41d22e81dceb1aff6daadeb328afc236d43b3359eb20ece8b

Observation 403508a8-884e-471d-b580-c8aa5b952fa1 · outbound

This paper cites Sdr–half-baked or well done?.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Sdr–half-baked or well done?

Reference 13

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raw_fallback, observed 2026-08-12T11:12:18.605597Z

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.

source=pdf_text observed=2026-08-12T11:12:17.993759Z digest=sha256:3bdbd8987f7a52a3d57d10eceb43cbbdbc0721737314f43a73f7f2cf16637a76

Observation fe2a0365-d571-44f5-8da0-4a6effd92f26 · outbound

This paper cites Joint optimization of masks and deep recurrent neural networks for monaural source separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Joint optimization of masks and deep recurrent neural networks for monaural source separation,

Reference 14

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raw_fallback, observed 2026-08-12T11:12:18.594092Z

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.

source=pdf_text observed=2026-08-12T11:12:17.997086Z digest=sha256:0fade52e69055bbb82f5fe82ee5df65d37d03ca1253afe502d16cb670facc947

Observation 14abe082-9809-4412-aae3-922780083853 · outbound

This paper cites Deep neural networks for single-channel multi-talker speech recognition,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Deep neural networks for single-channel multi-talker speech recognition,

Reference 15

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raw_fallback, observed 2026-08-12T11:12:18.583478Z

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.

source=pdf_text observed=2026-08-12T11:12:18.000753Z digest=sha256:9bf61300671aa6baa4c1d2614656805a9c037294c7e11c6dbdfc29fda6b58745

Observation b67869a5-d6bf-4b87-a126-647f4144033d · outbound

This paper cites Deep clustering: Discriminative embeddings for segmentation and separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Deep clustering: Discriminative embeddings for segmentation and separation,

Reference 16

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raw_fallback, observed 2026-08-12T11:12:18.572297Z

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.

source=pdf_text observed=2026-08-12T11:12:18.003650Z digest=sha256:2a231c0ec2a4ab7cdd58b0ad20abd3569c33de00e3d5a05f42f345e115468d40

Observation 26572624-61b1-4b77-9860-649a277ff3d9 · outbound

This paper cites Deep attractor network for single- microphone speaker separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Deep attractor network for single- microphone speaker separation,

Reference 17

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raw_fallback, observed 2026-08-12T11:12:18.562151Z

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.

source=pdf_text observed=2026-08-12T11:12:18.006696Z digest=sha256:798aa5b4631ecff31064373a3ec334fe537d6c06c12259650c9ca10b92a50335

Observation 0b52f99f-3e9f-45e2-9959-a2f596c01ec1 · outbound

This paper cites Permutation invariant training of deep models for speaker-independent multi-talker speech separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Permutation invariant training of deep models for speaker-independent multi-talker speech separation,

Reference 18

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raw_fallback, observed 2026-08-12T11:12:18.550427Z

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.

source=pdf_text observed=2026-08-12T11:12:18.010792Z digest=sha256:4af8449fcaf2ce79f44bf5514db47a9fbeec03a5f4bea1fee3b15b24380d9be4

Observation 8b4b163b-dd9c-49b8-8a65-5cd1ae083833 · outbound

This paper cites Many-speakers single channel speech separation with optimal permutation training,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Many-speakers single channel speech separation with optimal permutation training,

Reference 19

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raw_fallback, observed 2026-08-12T11:12:18.538629Z

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.

source=pdf_text observed=2026-08-12T11:12:18.013949Z digest=sha256:02f8587ae5d3e26529728a32f120a77bfdfc6722b1b68eeadce225419aeaf734

Observation 1562ac92-a5e2-47b9-b845-4d5732b4cd67 · outbound

This paper cites Theoretical improvements in algorithmic efficiency for network flow problems,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Theoretical improvements in algorithmic efficiency for network flow problems,

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.017104Z digest=sha256:2ff0372eb8e4c23efc0861beab5746ef00a4a28b676d93ca7c6877affd51b82a

Observation d204ad37-7768-4a6e-a18b-4cd67d047354 · outbound

This paper cites Towards listening to 10 people simultaneously: An efficient permutation invariant training of audio source separation using sinkhorn’s algorithm,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Towards listening to 10 people simultaneously: An efficient permutation invariant training of audio source separation using sinkhorn’s algorithm,

Reference 21

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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.

source=pdf_text observed=2026-08-12T11:12:18.019963Z digest=sha256:c6edc7618c698e77a47d7c02b5be6ecec1a4d8d6b14c2a60220b4a3d401f237b

Observation 73f0a81e-a3ff-494c-9e9e-3bf9622d48f4 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Sinkhorn distances: Lightspeed computation of optimal transport,

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.023631Z digest=sha256:388ab6e50463a04bf989a529f4d230642eeb9950e63fa6c289aca8bd2e5d00c1

Observation 352f6fcf-2f53-4f75-bb99-286180d5ba44 · outbound

This paper cites Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing

Reference 23

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local_arxiv, observed 2026-08-12T11:12:18.276878Z

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.

source=pdf_text observed=2026-08-12T11:12:18.026727Z digest=sha256:a67aaeb01335b8838eafd1b3c431c8f490f83b0b33570505348353e543f0360b

Observation bbc9cfb6-26e6-4f27-b2cf-44845fb78c7b · outbound

This paper cites Multiple choice learning: Learning to produce multiple structured outputs,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Multiple choice learning: Learning to produce multiple structured outputs,

Reference 24

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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.

source=pdf_text observed=2026-08-12T11:12:18.030404Z digest=sha256:0f09d6bd902fc61ff31d244d3363bfe645ffc2738982e736b81cb4f76e870270

Observation 12ed9720-398e-4e3c-a913-80c4797c9ede · outbound

This paper cites Stochastic multiple choice learning for training diverse deep ensembles,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Stochastic multiple choice learning for training diverse deep ensembles,

Reference 25

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raw_fallback, observed 2026-08-12T11:12:18.492430Z

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.

source=pdf_text observed=2026-08-12T11:12:18.033473Z digest=sha256:5994cd3bd34dd187ff7ca701350dcec94c14b16fd4fedb101422ca562dbf9a66

Observation 26a0f539-bdd0-4b45-9fb1-b13c20185f9f · outbound

This paper cites Dsmcl: Dual-level stochas- tic multiple choice learning for multi-modal trajectory prediction,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Dsmcl: Dual-level stochas- tic multiple choice learning for multi-modal trajectory prediction,

Reference 26

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raw_fallback, observed 2026-08-12T11:12:18.481328Z

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.

source=pdf_text observed=2026-08-12T11:12:18.037556Z digest=sha256:c3797cab47d544bfaa257639d9373b48c67542efd789b41b168b5d35bb65a29e

Observation 566b3b04-ee96-40da-978c-b27c15a92945 · outbound

This paper cites V oice separation with an unknown number of multiple speakers,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers V oice separation with an unknown number of multiple speakers,

Reference 27

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raw_fallback, observed 2026-08-12T11:12:18.470285Z

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.

source=pdf_text observed=2026-08-12T11:12:18.040720Z digest=sha256:68ee2cb69258424ace3f9176e7f7958e031b9e84220fbcb7df80341c7e3b8d0a

Observation b541b667-b5c6-4505-94e5-da79b30a2cbc · outbound

This paper cites Least squares quantization in pcm,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Least squares quantization in pcm,

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.044321Z digest=sha256:1fa3b45d66a8131caf023d96b8c9b8f953adedaf4650990bcc6536107aada0f5

Observation 96693ff2-2002-4b2e-b543-c2b7a1a374f4 · outbound

This paper cites Learning in an uncertain world: Representing ambiguity through multiple hypotheses,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Learning in an uncertain world: Representing ambiguity through multiple hypotheses,

Reference 29

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raw_fallback, observed 2026-08-12T11:12:18.454969Z

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.

source=pdf_text observed=2026-08-12T11:12:18.047520Z digest=sha256:049a703813f24c7e8d3c58f92ef8719d2d15d7fb80fde8273783b87a1d7e266f

Observation 06a52b33-ee20-4967-bd55-5f50280b74fd · outbound

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

Multiple Choice Learning for Efficient Speech Separation with Many Speakers LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.051999Z digest=sha256:9843a17c455c5926f6874c1bf12e175e603df473e0d0ec3f32f9cb49724dca39

Observation 463f3241-96f7-4a0b-a2cb-6ac0effb008e · outbound

This paper cites Conv-tasnet: Surpassing ideal time– frequency magnitude masking for speech separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Conv-tasnet: Surpassing ideal time– frequency magnitude masking for speech separation,

Reference 31

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no resolver link, observed 2026-08-12T11:12:18.055529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.055529Z digest=sha256:ff0f5bb0ba50f099c811c588b8604cd77a865f84a2551ed5c77b6aa6d4e59593

Observation 62031daf-4687-48d5-9368-e05a9c5af0d0 · outbound

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

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Dual-path RNN: Efficient long sequence modeling for time-domain single-channel speech separation,

Reference 32

Resolution
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raw_fallback, observed 2026-08-12T11:12:18.250379Z

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.

source=pdf_text observed=2026-08-12T11:12:18.059556Z digest=sha256:1e5299d25dc722750834558681eedb858b06bb5b08985efe1997933350f3bddb

Observation 3f5363fd-80e1-4874-8838-5867d05ccee2 · outbound

This paper cites Attention is all you need in speech separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Attention is all you need in speech separation,

Reference 33

Resolution
verified exact
raw_fallback, observed 2026-08-12T11:12:18.185169Z

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.

source=pdf_text observed=2026-08-12T11:12:18.062766Z digest=sha256:7a5d7b527b60e329fb51ad89ccfde27bdc8008c1ab3d6b1f2d983798ac3f2363

Observation a283212a-37f8-4ad6-93a3-90be41c60db1 · outbound

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

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Mossformer: Pushing the performance limit of monaural speech separation using gated single-head transformer with convolution-augmented joint self-attentions,

Reference 34

Resolution
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raw_fallback, observed 2026-08-12T11:12:18.438809Z

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.

source=pdf_text observed=2026-08-12T11:12:18.066414Z digest=sha256:b1cbface4d7f8e54d7b416b869f243a1438abc17805e38436886ed99e9458728

Observation d9a66a66-cc06-4727-8657-ccd309c27f98 · outbound

This paper cites Tf-gridnet: Integrating full-and sub-band modeling for speech separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Tf-gridnet: Integrating full-and sub-band modeling for speech separation,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T11:12:18.069514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:12:18.069514Z digest=sha256:9aa582151cffff0e41d319a5a2af8d7e093287561b87520863bc24d40888c3b5

Observation 26c1d038-2237-4e16-92f7-e85f293e8eec · outbound

This paper cites Universal sound separation,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Universal sound separation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.422551Z

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.

source=pdf_text observed=2026-08-12T11:12:18.073584Z digest=sha256:e5ff9294da3bdbe856f7bac8f2aabd04e3c213f9419d046fb79e913c2f28b4de

Observation d37c1083-977a-446b-b388-1274ac9195e3 · outbound

This paper cites Signal source separation in the analysis of neural activity in brain,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Signal source separation in the analysis of neural activity in brain,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.411715Z

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.

source=pdf_text observed=2026-08-12T11:12:18.076701Z digest=sha256:942d8e4998ad2e5f30aa1fcbd66c6b78a0ed23d74576ee7558ccaf37de8beb26

Observation 02303274-6974-41f0-aeba-dd64c3473cfd · outbound

This paper cites Deep neural network techniques for monaural speech enhancement and separation: state of the art analysis,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Deep neural network techniques for monaural speech enhancement and separation: state of the art analysis,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.399736Z

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.

source=pdf_text observed=2026-08-12T11:12:18.080700Z digest=sha256:ac81a9e7551961e55bc814a392b8805d4874ab8a50df4b27f7be1b91335fd1d0

Observation 564e0e2b-85a9-4b8b-bc39-e925178c6257 · outbound

This paper cites Resilient multiple choice learning: A learned scoring scheme with application to audio scene analysis,.

Multiple Choice Learning for Efficient Speech Separation with Many Speakers Resilient multiple choice learning: A learned scoring scheme with application to audio scene analysis,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:12:18.387048Z

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.

source=pdf_text observed=2026-08-12T11:12:18.083831Z digest=sha256:5e91fa507d3bb64ea445d84f2cf1257c686e289d5f3020e7bf81535972535e87

Pith citing papers

No inbound Pith citation observations are available.