Paper Citation Record · LEDGER

Multiple Choice Learning for Efficient Speech Separation with Many Speakers

As of 13 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 2026-08-12T06:34:41.77262+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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:17.975216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:17.982608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:17.985998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:17.989908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:18.017104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:12:18.521417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:18.023631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified exact; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:12:18.503725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:18.044321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T11:12:18.051999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: verified exact; 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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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: verified fuzzy; 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 2026-08-12T06:34:41.77262+00:00.

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.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.