From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition | Paper Citation Record

Observation 749b4bef-0a31-4856-a0bc-f8e3aeb8a981 · outbound

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition online" 'onlinestring :=

Reference 1

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition write newline

Reference 2

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 3

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 4

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Observation 51065def-f9b0-4641-bc23-c1fe90918aba · outbound

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

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Common Voice: A Massively-Multilingual Speech Corpus

Reference 5

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Synthetic Data from Diffusion Models Improves ImageNet Classification

Reference 6

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 7

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 8

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Observation 463240d4-c012-4afd-8079-e7ebc5705b0d · outbound

This paper cites wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:54.314575Z

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Observation 888acafe-876e-438d-99b9-60c6a4d3cabd · outbound

This paper cites Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:54.427250Z

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 11

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This paper cites an unresolved cited work.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 12

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Observation fb412036-97d5-4785-9018-d1fe2474c66e · outbound

This paper cites XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:54.665380Z

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Observation 9b65f5b2-3f11-49c6-800e-ef63fd2fe423 · outbound

This paper cites Towards Robust Speech Representation Learning for Thousands of Languages.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Towards Robust Speech Representation Learning for Thousands of Languages

Reference 14

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Observation ae97234f-0160-422c-af4e-9c536861be1f · outbound

This paper cites Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent

Reference 15

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Observation 851d97c0-f3eb-4d2c-b8c6-bb67bb7072d4 · outbound

This paper cites Seamless: Multilingual Expressive and Streaming Speech Translation.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Seamless: Multilingual Expressive and Streaming Speech Translation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:54.912281Z

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:03.105039Z

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Observation 3c0638db-9725-4da7-8d96-67e4b858b084 · outbound

This paper cites No Language Left Behind: Scaling Human-Centered Machine Translation.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition No Language Left Behind: Scaling Human-Centered Machine Translation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:55.065966Z

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Observation bb08feb4-246b-4e5e-b096-79b083b6457d · outbound

This paper cites CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:55:59.809037Z

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Observation 42604363-4e17-44da-9d12-57971fd4abbc · outbound

This paper cites Understanding Back-Translation at Scale.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Understanding Back-Translation at Scale

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:55.225525Z

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Observation 614ab78c-b34f-489d-b9a8-3d7585b2a781 · outbound

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 21

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Observation d695a88a-0cf4-4a2e-9a08-59f3d2684eed · outbound

This paper cites Hasegawa-Johnson, Shiyu Chang, and Yang Zhang.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Hasegawa-Johnson, Shiyu Chang, and Yang Zhang

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:02.806913Z

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Observation d9558d3f-fb26-44cf-af03-08a9bafb6415 · outbound

This paper cites Textbooks Are All You Need.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Textbooks Are All You Need

Reference 23

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 24

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Observation aa6c3185-dcb8-4aa5-93ae-5dd8727a85ab · outbound

This paper cites Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation

Reference 25

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 26

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Observation edee7b2d-1094-48e3-9e5f-16779cfea925 · outbound

This paper cites Speech Translation with Large Language Models: An Industrial Practice.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Speech Translation with Large Language Models: An Industrial Practice

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:55.748608Z

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This paper cites an unresolved cited work.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 28

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This paper cites HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

Reference 29

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 30

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This paper cites Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 31

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 32

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Observation 0a8853c1-bc77-4cc2-b259-aa41ef251803 · outbound

This paper cites Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters

Reference 33

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

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Scaling Speech Technology to 1,000+ Languages

Reference 34

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This paper cites MLS: A Large-Scale Multilingual Dataset for Speech Research.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition MLS: A Large-Scale Multilingual Dataset for Speech Research

Reference 35

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This paper cites Less is More: Accurate Speech Recognition & Translation without Web-Scale Data.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Less is More: Accurate Speech Recognition & Translation without Web-Scale Data

Reference 36

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Observation 7489012e-c329-4f5a-8be7-8331d9ac307c · outbound

This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Robust Speech Recognition via Large-Scale Weak Supervision

Reference 37

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Reference 38

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This paper cites Blattmann, Dominik Lorenz, Patrick Esser, and Bj \"o rn Ommer.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Blattmann, Dominik Lorenz, Patrick Esser, and Bj \"o rn Ommer

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:01.810253Z

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Observation 31a069dc-96b6-4896-b176-9adfe6b9f8b1 · outbound

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Reference 40

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 41

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Observation fa95a800-6595-417b-af9a-f94e5bea44ef · outbound

This paper cites Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis

Reference 42

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 43

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Observation f7a78e29-80ab-4c3d-b9aa-f77f7ab8bf71 · outbound

This paper cites StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

Reference 44

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition LLaMA: Open and Efficient Foundation Language Models

Reference 45

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 46

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Effective Data Augmentation With Diffusion Models

Reference 47

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This paper cites VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation

Reference 48

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Observation 9dd89f1e-ac5d-4aed-99c1-9262f5d8728a · outbound

This paper cites Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

Reference 49

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 50

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Observation 0b620978-fab8-4bfd-927c-dcf3d9c6e675 · outbound

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 51

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Observation cb572e1c-c837-40e5-b3bf-23355b8c2610 · outbound

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 52

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Observation 298d3a94-989d-42fc-ba0b-9a1891f70374 · outbound

This paper cites Skywork: A More Open Bilingual Foundation Model.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Skywork: A More Open Bilingual Foundation Model

Reference 53

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This paper cites Enhancing Low-Resource ASR through Versatile TTS: Bridging the Data Gap.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Enhancing Low-Resource ASR through Versatile TTS: Bridging the Data Gap

Reference 54

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Observation 230d8c32-385a-4d69-bc79-a1f6c7215863 · outbound

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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 55

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Observation ed7f5382-0d3b-4d65-a29d-a64967f2ff51 · outbound

This paper cites an unresolved cited work.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:00.411285Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 04e01395-1449-4357-81d7-0b687c7b1a02 · outbound

This paper cites an unresolved cited work.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:56:00.263139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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