Paper Citation Record · LEDGER

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.05759.

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

pith.paper-citation-record.v1
2608.05759 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:37:54.861443Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

34 of 34 outbound references displayed

verified exact0
verified fuzzy19
unresolved15
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0488faff-ce29-4ca6-a2de-6cb2cc13afde · outbound

This paper cites Attention is all you need,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Attention is all you need,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.753711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f83f31c8-b898-41b9-9946-fb80c9d7f038 · outbound

This paper cites Very Deep Self-Attention Networks for End-to-End Speech Recognition.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Very Deep Self-Attention Networks for End-to-End Speech Recognition

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.757887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cee99dc-bf42-48c6-9305-c8fc38333c19 · outbound

This paper cites Robust speech recognition via large-scale weak supervi- sion,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Robust speech recognition via large-scale weak supervi- sion,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.761830Z

Source-reported events for the cited work

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Observation 19c4d942-8864-4dbd-a23a-fe686dcdf101 · outbound

This paper cites Cold fusion: Training seq2seq models together with language models,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Cold fusion: Training seq2seq models together with language models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.241834Z

Source-reported events for the cited work

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Observation 5349d334-eb75-49bd-9a0a-a2f2c63e3bd6 · outbound

This paper cites Contextual speech recognition in end-to-end neural network systems using beam search.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextual speech recognition in end-to-end neural network systems using beam search

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.231688Z

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Observation bd067287-f88d-45e7-90ce-19b0bdcab035 · outbound

This paper cites An analysis of incorporating an external language model into a sequence-to-sequence model,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs An analysis of incorporating an external language model into a sequence-to-sequence model,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.221986Z

Source-reported events for the cited work

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Observation 7817578e-d7a3-4b7d-9f74-7182dcfe6090 · outbound

This paper cites Class lm and word mapping for contextual biasing in end-to-end asr,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Class lm and word mapping for contextual biasing in end-to-end asr,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.212153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e0655cfc-a155-4741-9ed8-ae33d4f97853 · outbound

This paper cites A study of biasing technical terms in medical speech recognition using weighted finite-state transducer,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs A study of biasing technical terms in medical speech recognition using weighted finite-state transducer,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.201780Z

Source-reported events for the cited work

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Observation 9fafb509-6517-4c4b-b9f9-8f7abb4eb4fc · outbound

This paper cites Deep context: end-to-end contextual speech recognition,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Deep context: end-to-end contextual speech recognition,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.191911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a11b88ba-2aff-423a-8a05-c56a6e36450a · outbound

This paper cites Phoebe: Pronunciation-aware contextualization for end-to-end speech recogni- tion,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Phoebe: Pronunciation-aware contextualization for end-to-end speech recogni- tion,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.181705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5ba1f6ea-09a2-4657-b70a-0bdb87d9ea00 · outbound

This paper cites Contextual rnn-t for open domain asr,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextual rnn-t for open domain asr,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.170569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8209bf31-108d-47eb-8776-4c7e8eced7d0 · outbound

This paper cites Instant one-shot word- learning for context-specific neural sequence-to-sequence speech recog- nition,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Instant one-shot word- learning for context-specific neural sequence-to-sequence speech recog- nition,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.161013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2cb03cca-d3d7-4fa1-9b10-48f39bfc8b0f · outbound

This paper cites Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.795633Z

Source-reported events for the cited work

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Observation 3f4c6f7b-e99c-40b1-908f-f59221948cb5 · outbound

This paper cites Im- proving end-to-end contextual speech recognition with fine-grained con- textual knowledge selection,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Im- proving end-to-end contextual speech recognition with fine-grained con- textual knowledge selection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.151478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6f07d30b-e9e6-4926-a86f-a2ad53eb289a · outbound

This paper cites Personalization of ctc speech recognition models,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Personalization of ctc speech recognition models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.141377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5c3f9c2b-203c-41e4-8d50-4a8758255728 · outbound

This paper cites Contextualized end-to-end speech recognition with contextual phrase prediction network,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextualized end-to-end speech recognition with contextual phrase prediction network,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.130903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90f1d509-2738-41b1-a994-eaa4b9813d70 · outbound

This paper cites Promptasr for contextualized asr with controllable style,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Promptasr for contextualized asr with controllable style,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.121032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1722ddd1-e807-4180-a8c2-df41db7e6960 · outbound

This paper cites Contex- tualized automatic speech recognition with attention-based bias phrase boosted beam search,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contex- tualized automatic speech recognition with attention-based bias phrase boosted beam search,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.111017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e83321ee-8421-4e9d-ac21-ea0ff12ce3f2 · outbound

This paper cites Lcb-net: Long-context bias- ing for audio-visual speech recognition,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Lcb-net: Long-context bias- ing for audio-visual speech recognition,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.100922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 116c156a-b541-4f6a-9dfc-f2b5473f532f · outbound

This paper cites Contextual asr with retrieval augmented large language model,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextual asr with retrieval augmented large language model,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.090344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation aa094b2b-8a67-4b87-8d37-f407afa44880 · outbound

This paper cites OWSM-Biasing: Contextualizing Open Whisper-Style Speech Models for Automatic Speech Recognition with Dynamic Vocabulary.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs OWSM-Biasing: Contextualizing Open Whisper-Style Speech Models for Automatic Speech Recognition with Dynamic Vocabulary

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.821097Z

Source-reported events for the cited work

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Observation 5db425e7-7d95-4342-b523-66829189067c · outbound

This paper cites Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.824366Z

Source-reported events for the cited work

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Observation 199ef8c5-fd3e-4ff6-9bda-eb2f6c01ca10 · outbound

This paper cites Salmonn: Towards generic hearing abilities for large language models,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Salmonn: Towards generic hearing abilities for large language models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.827387Z

Source-reported events for the cited work

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Observation b70be1a4-c221-421c-a3ab-aa48dead33b6 · outbound

This paper cites Wavllm: Towards robust and adaptive speech large language model,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Wavllm: Towards robust and adaptive speech large language model,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.830633Z

Source-reported events for the cited work

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Observation fd026fbb-fa4a-4ca8-9ce6-a76ca54d9a47 · outbound

This paper cites End-to-end speech recognition contextualization with large language models,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs End-to-end speech recognition contextualization with large language models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.068402Z

Source-reported events for the cited work

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Observation d2d9e38b-c99b-4d91-8d6c-3d0c91bbdbfa · outbound

This paper cites Contextual biasing speech recognition in speech-enhanced large language model.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Contextual biasing speech recognition in speech-enhanced large language model

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.057708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 24ff465f-c8ce-4d40-811b-3c44d8deacf7 · outbound

This paper cites Qwen3-ASR Technical Report.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Qwen3-ASR Technical Report

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.839441Z

Source-reported events for the cited work

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Observation c878dd91-2cf5-408b-b15c-aa833db4a768 · outbound

This paper cites Qwen3-Omni Technical Report.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Qwen3-Omni Technical Report

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.842666Z

Source-reported events for the cited work

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Observation db43992d-571f-40fc-935f-8ad1dff5a7bb · outbound

This paper cites Vibevoice-asr technical report,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Vibevoice-asr technical report,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.846000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b000b07-c96f-47d4-b803-7310d9f3f5f7 · outbound

This paper cites Multilingual Translation with Extensible Multilingual Pretraining and Finetuning.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Multilingual Translation with Extensible Multilingual Pretraining and Finetuning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.848891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55049e77-e4df-402f-b48a-b1c9bed06c89 · outbound

This paper cites Common Voice: A Massively-Multilingual Speech Corpus.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Common Voice: A Massively-Multilingual Speech Corpus

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.851988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e103ab0-9c4b-4c74-bf42-85c97da94003 · outbound

This paper cites Earnings-21: A Practical Benchmark for ASR in the Wild.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Earnings-21: A Practical Benchmark for ASR in the Wild

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.855049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da10b423-ff19-472a-a23d-0347c1ea6817 · outbound

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

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Librispeech: an asr corpus based on public domain audio books,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:54.858357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a488f792-c10e-4674-ad68-3b047976ecbd · outbound

This paper cites Yodas: Youtube-oriented dataset for audio and speech,.

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs Yodas: Youtube-oriented dataset for audio and speech,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:37:55.040695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.