Paper Citation Record · LEDGER

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data

As of 17 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2501.12501.

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

pith.paper-citation-record.v1
2501.12501 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:12:09.688401Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T17:15:32.992695Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T07:15:59.760491Z

Reference resolution

20 of 20 outbound references displayed

verified exact0
verified fuzzy8
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 599554e6-500f-498e-b591-0cd13d527d5d · outbound

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

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Robust speech recognition via large-scale weak supervision,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.586904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fe0b449-d69f-404f-8339-4e060e68e925 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Lora: Low-rank adaptation of large language models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:10.024001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df23c583-ddae-43f8-82f0-71293a119dd4 · outbound

This paper cites An unsupervised deep domain adaptation approach for robust speech recognition,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data An unsupervised deep domain adaptation approach for robust speech recognition,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:10.005635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fcd97461-b314-428e-bb68-c52db0b45e01 · outbound

This paper cites Unsupervised domain adaptation by backpropagation,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Unsupervised domain adaptation by backpropagation,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.602169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcd9ed74-2d2e-429a-9941-46b921196731 · outbound

This paper cites Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmen- tation,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmen- tation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.977178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 35b5347d-de99-4a1e-a147-2660fafe1d76 · outbound

This paper cites Domain adaptation via teacher- student learning for end-to-end speech recognition,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Domain adaptation via teacher- student learning for end-to-end speech recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.960137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e3fd4c0b-64ac-48e2-8700-4a490f02caf8 · outbound

This paper cites Domain adaptation of end-to- end speech recognition in low-resource settings,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Domain adaptation of end-to- end speech recognition in low-resource settings,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.943550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d78f38cc-bb48-4bfc-9e6f-2759e8698718 · outbound

This paper cites Domain adaptation using factorized hidden layer for robust automatic speech recognition.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Domain adaptation using factorized hidden layer for robust automatic speech recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.927903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6a12a86f-c03a-4137-9b2a-71bf20270839 · outbound

This paper cites A comparison of parameter-efficient asr domain adaptation methods for universal speech and language models,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data A comparison of parameter-efficient asr domain adaptation methods for universal speech and language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.911841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b6c511c0-6dcb-4e0f-9415-e9cd3c4d533f · outbound

This paper cites Learning multiple visual do- mains with residual adapters,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Learning multiple visual do- mains with residual adapters,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.633063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2efa35d7-e524-4089-91ae-55e4603047d4 · outbound

This paper cites Using synthetic audio to improve the recognition of out-of-vocabulary words in end-to-end asr systems,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Using synthetic audio to improve the recognition of out-of-vocabulary words in end-to-end asr systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:12:09.881087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a108cc30-fac5-4bbe-aa67-df0c9c7099a6 · outbound

This paper cites Text Generation with Speech Synthesis for ASR Data Augmentation.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Text Generation with Speech Synthesis for ASR Data Augmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.644429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac914ec3-ac0a-4942-9560-7bbfc94212a0 · outbound

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

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.651132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31cedbf6-8316-4eb2-8cf5-eb17aa68fab7 · outbound

This paper cites Llama 3 model card,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Llama 3 model card,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.656618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0e91473-4f47-4bc8-96ce-b0218d178772 · outbound

This paper cites CodecLM: Aligning Language Models with Tailored Synthetic Data.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data CodecLM: Aligning Language Models with Tailored Synthetic Data

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.661664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9ca3bec-4a11-4c42-a3c6-4a10a5d68682 · outbound

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

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Librispeech: an asr corpus based on public domain audio books,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.667897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44411f63-58af-4223-b4b3-d491c9c25841 · outbound

This paper cites Attention is all you need,.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data Attention is all you need,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.672987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b01641e0-3dc6-442f-86be-453017073497 · outbound

This paper cites S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.678075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b13ba55-2bab-41b6-b294-fc2fe34732d5 · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.683120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab50c507-eaf4-46d2-b91c-fab6c3e40cb9 · outbound

This paper cites PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models.

A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T17:12:09.688401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 54d15839-e2c7-4e5c-9bf1-4cb8645c9654 · inbound

Enhancing ASR Performance in the Medical Domain for Dravidian Languages cites this paper.

Enhancing ASR Performance in the Medical Domain for Dravidian Languages A Domain Adaptation Framework for Speech Recognition Systems with Only Synthetic data

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:15:59.770969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.