Paper Citation Record · LEDGER

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition

As of 13 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2411.17537.

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

pith.paper-citation-record.v1
2411.17537 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:13:11.939403Z

measured 27 of 27 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

27 of 27 outbound references displayed

verified exact1
verified fuzzy21
unresolved5
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d1fb53bf-ccba-4b84-8587-837ac432bed3 · outbound

This paper cites Improving proper noun recog- nition in end-to-end asr by customization of the mwer loss criterion,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Improving proper noun recog- nition in end-to-end asr by customization of the mwer loss criterion,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.383662Z

Source-reported events for the cited work

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Observation 171e2db0-00b3-48bc-b65f-c505cbef4ef0 · outbound

This paper cites Personalization of end-to-end speech recognition on mobile devices for named entities,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Personalization of end-to-end speech recognition on mobile devices for named entities,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.367127Z

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 b12b8d2b-9278-414c-878c-72d4e96a80d5 · outbound

This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T12:13:11.826465Z

Source-reported events for the cited work

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Observation a600b9bd-bfdb-40d5-8f86-e50a9f9d4cc9 · outbound

This paper cites Scaling Speech Technology to 1,000+ Languages.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Scaling Speech Technology to 1,000+ Languages

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T12:13:11.831434Z

Source-reported events for the cited work

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Observation 7cad08d1-e2ab-45dd-aa9a-37f66686eb3a · outbound

This paper cites A better and faster end-to- end model for streaming asr,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition A better and faster end-to- end model for streaming asr,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.350590Z

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 8d1623b1-1960-4911-9663-a6a033a65439 · outbound

This paper cites Cascaded encoders for unifying streaming and non-streaming asr,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Cascaded encoders for unifying streaming and non-streaming asr,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.335630Z

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 6f2010c9-a873-4e92-b3ba-2c06ffbcbeff · outbound

This paper cites Dual-mode asr: Unify and improve streaming asr with full-context modeling,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Dual-mode asr: Unify and improve streaming asr with full-context modeling,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.320471Z

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 5a344ed2-2b68-45de-9f4d-a90fc9b05648 · outbound

This paper cites Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,

Reference 8

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Source-reported events for the cited work

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Observation b46cab54-a763-478d-a4e9-e98026def95a · outbound

This paper cites Connectionist temporal classification: labelling unsegmented sequence data with recur- rent neural networks,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Connectionist temporal classification: labelling unsegmented sequence data with recur- rent neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.294940Z

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 d4108838-eac7-4adb-9417-b30939bcd4d3 · outbound

This paper cites Sequence transduction with recurrent neural networks,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Sequence transduction with recurrent neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.279887Z

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 0b875d82-d58c-4c7a-9d4b-53ce49212ab7 · outbound

This paper cites End-to-end attention-based large vocabulary speech recognition,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition End-to-end attention-based large vocabulary speech recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.263759Z

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 3e4a5c99-a609-41d8-b611-ac70dfbab78f · outbound

This paper cites Listen, attend and spell: A neural network for large vocabulary conversational speech recognition,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Listen, attend and spell: A neural network for large vocabulary conversational speech recognition,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.249338Z

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 4d9306e7-1ed0-4a94-89ec-db00dc4286a2 · outbound

This paper cites CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:13:12.016770Z

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 10e80c2f-73f4-4c60-b04a-aa19bcfc006b · outbound

This paper cites Crf-based single-stage acoustic modeling with ctc topology,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Crf-based single-stage acoustic modeling with ctc topology,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.234353Z

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 5903ca51-3a82-4b88-a792-a8a449583128 · outbound

This paper cites Imputer: Sequence modelling via imputation and dynamic programming,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Imputer: Sequence modelling via imputation and dynamic programming,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.219564Z

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 e9b2fdcd-caf4-44c9-880f-b99446e699a6 · outbound

This paper cites Global normalization for streaming speech recognition in a modular framework,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Global normalization for streaming speech recognition in a modular framework,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.204049Z

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 c55bfd57-f5ec-470f-bc88-34313b235760 · outbound

This paper cites An unsupervised autoregressive model for speech representation learning,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition An unsupervised autoregressive model for speech representation learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.189145Z

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 7d281fd7-cbe5-4a1f-9e41-fb57c8f17546 · outbound

This paper cites Variational inference with normalizing flows,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Variational inference with normalizing flows,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.174075Z

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 0d4597f1-bc0a-447f-9fe8-b7d039341609 · outbound

This paper cites https://github.com/k2-fsa/icefall.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition https://github.com/k2-fsa/icefall

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.158985Z

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 7eef7b32-dfc2-4500-b436-de80460cd04d · outbound

This paper cites Librispeech: an asr corpus based on public domain audio books,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Librispeech: an asr corpus based on public domain audio books,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.143688Z

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 343bbec1-16af-49d8-8430-fb1ee3a486aa · outbound

This paper cites Ted-lium 3: Twice as much data and corpus repartition for experiments on speaker adaptation,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Ted-lium 3: Twice as much data and corpus repartition for experiments on speaker adaptation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.127432Z

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 74753a00-dfa4-4b74-83f1-23b4aadd3664 · outbound

This paper cites A new algorithm for data compression,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition A new algorithm for data compression,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.112275Z

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 1f671f66-86ad-4e7b-84ce-7b688cad4f50 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Neural Machine Translation of Rare Words with Subword Units

Reference 23

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Source-reported events for the cited work

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Observation 28b369b5-17ba-4972-859f-618ccaef638b · outbound

This paper cites Zipformer: A faster and better encoder for automatic speech recognition.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Zipformer: A faster and better encoder for automatic speech recognition

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T12:13:11.925137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 250cd683-1af0-4a57-91ea-0b7d501eabd6 · outbound

This paper cites Rnn- transducer with stateless prediction network,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Rnn- transducer with stateless prediction network,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.097217Z

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 011b3b63-fd94-4e61-8ad7-803d89938d9e · outbound

This paper cites Made: Masked autoencoder for distribution estimation,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Made: Masked autoencoder for distribution estimation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.081969Z

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 42beed4c-1604-49a0-8c7b-e468d514b2cb · outbound

This paper cites Specaugment: A simple data augmentation method for automatic speech recognition,.

Towards Maximum Likelihood Training for Transducer-based Streaming Speech Recognition Specaugment: A simple data augmentation method for automatic speech recognition,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:13:12.066442Z

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.