{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/automatic-speech-recognition-2/papers/11","list_of":"/task/automatic-speech-recognition-2","task":"Automatic Speech Recognition","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":11,"pages_in_order":32,"rows_per_page":100,"rows":[1001,1100],"of":3174,"counts":{"archive_papers_tagged":3174,"with_a_code_link":677,"where_syntology_ran_a_sample":79,"not_listed_spam_title":0,"listed":3174,"listed_where_code_ran":79,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":62,"every_run_a_failure_of_syntologys_instrument":17,"listed_with_a_run_with_no_instrument_failure":62,"listed_every_run_a_failure_of_syntologys_instrument":17,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/automatic-speech-recognition-2","prev":"/task/automatic-speech-recognition-2/papers/10","next":"/task/automatic-speech-recognition-2/papers/12","papers":[{"url":null,"slug":"medsage-enhancing-robustness-of-medical","title":"MEDSAGE: Enhancing Robustness of Medical Dialogue Summarization to ASR Errors with LLM-generated Synthetic Dialogues","date":"2024-08-26","arxiv_id":"2408.14418","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-advances-and-new-paradigms-for","title":"Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks","date":"2024-08-26","arxiv_id":"2408.13996","repositories_listed":0,"syntology":null},{"url":null,"slug":"focused-discriminative-training-for-streaming","title":"Focused Discriminative Training For Streaming CTC-Trained Automatic Speech Recognition Models","date":"2024-08-23","arxiv_id":"2408.13008","repositories_listed":0,"syntology":null},{"url":null,"slug":"developing-vocal-system-impaired-patient","title":"Developing vocal system impaired patient-aimed voice quality assessment approach using ASR representation-included multiple features","date":"2024-08-22","arxiv_id":"2408.12279","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-state-of-commercial-automatic-french","title":"The State of Commercial Automatic French Legal Speech Recognition Systems and their Impact on Court Reporters et al","date":"2024-08-21","arxiv_id":"2408.11940","repositories_listed":0,"syntology":null},{"url":null,"slug":"parameter-efficient-transfer-learning-under","title":"Parameter-Efficient Transfer Learning under Federated Learning for Automatic Speech Recognition","date":"2024-08-19","arxiv_id":"2408.11873","repositories_listed":0,"syntology":null},{"url":null,"slug":"recording-for-eyes-not-echoing-to-ears","title":"Recording for Eyes, Not Echoing to Ears: Contextualized Spoken-to-Written Conversion of ASR Transcripts","date":"2024-08-19","arxiv_id":"2408.09688","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-large-language-model-based-speech","title":"Enhancing Large Language Model-based Speech Recognition by Contextualization for Rare and Ambiguous Words","date":"2024-08-15","arxiv_id":"2408.08027","repositories_listed":0,"syntology":null},{"url":null,"slug":"dpsnn-spiking-neural-network-for-low-latency","title":"DPSNN: Spiking Neural Network for Low-Latency Streaming Speech Enhancement","date":"2024-08-14","arxiv_id":"2408.07388","repositories_listed":0,"syntology":null},{"url":null,"slug":"style-talker-finetuning-audio-language-model","title":"Style-Talker: Finetuning Audio Language Model and Style-Based Text-to-Speech Model for Fast Spoken Dialogue Generation","date":"2024-08-13","arxiv_id":"2408.11849","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-enhancement-for-computer-audition-an","title":"Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance","date":"2024-08-12","arxiv_id":"2408.06264","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-dialogue-speech-recognition-with","title":"Enhancing Dialogue Speech Recognition with Robust Contextual Awareness via Noise Representation Learning","date":"2024-08-12","arxiv_id":"2408.06043","repositories_listed":0,"syntology":null},{"url":null,"slug":"vq-ctap-cross-modal-fine-grained-sequence","title":"VQ-CTAP: Cross-Modal Fine-Grained Sequence Representation Learning for Speech Processing","date":"2024-08-11","arxiv_id":"2408.05758","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-whisper-s-recognition-performance","title":"Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text","date":"2024-08-10","arxiv_id":"2408.05554","repositories_listed":0,"syntology":null},{"url":"/paper/mathbridge-a-large-scale-dataset-for","slug":"mathbridge-a-large-scale-dataset-for","title":"MathBridge: A Large Corpus Dataset for Translating Spoken Mathematical Expressions into $LaTeX$ Formulas for Improved Readability","date":"2024-08-07","arxiv_id":"2408.07081","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02945","title":"Self-Supervised Learning for Multi-Channel Neural Transducer","date":"2024-08-06","arxiv_id":"2408.02945","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02978","title":"ASR-enhanced Multimodal Representation Learning for Cross-Domain Product Retrieval","date":"2024-08-06","arxiv_id":"2408.02978","repositories_listed":0,"syntology":null},{"url":null,"slug":"streamvoice-evolving-into-end-to-end","title":"StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion","date":"2024-08-05","arxiv_id":"2408.02178","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00205","title":"Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation","date":"2024-08-01","arxiv_id":"2408.00205","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21414","title":"Towards interfacing large language models with ASR systems using confidence measures and prompting","date":"2024-07-31","arxiv_id":"2407.21414","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21476","title":"On the Problem of Text-To-Speech Model Selection for Synthetic Data Generation in Automatic Speech Recognition","date":"2024-07-31","arxiv_id":"2407.21476","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21061","title":"Improving noisy student training for low-resource languages in End-to-End ASR using CycleGAN and inter-domain losses","date":"2024-07-26","arxiv_id":"2407.21061","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-domain-specific-asr-with-llm","title":"Improving Domain-Specific ASR with LLM-Generated Contextual Descriptions","date":"2024-07-25","arxiv_id":"2407.17874","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-effect-of-purely-synthetic-training","title":"On the Effect of Purely Synthetic Training Data for Different Automatic Speech Recognition Architectures","date":"2024-07-25","arxiv_id":"2407.17997","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-analysis-of-bilingual-and","title":"A Comparative Analysis of Bilingual and Trilingual Wav2Vec Models for Automatic Speech Recognition in Multilingual Oral History Archives","date":"2024-07-24","arxiv_id":"2407.17160","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-the-role-of-textual","title":"Quantifying the Role of Textual Predictability in Automatic Speech Recognition","date":"2024-07-23","arxiv_id":"2407.16537","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-chime-8-dasr-challenge-for-generalizable","title":"The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization","date":"2024-07-23","arxiv_id":"2407.16447","repositories_listed":0,"syntology":null},{"url":null,"slug":"trading-devil-final-backdoor-attack-via-stock","title":"Trading Devil Final: Backdoor attack via Stock market and Bayesian Optimization","date":"2024-07-21","arxiv_id":"2407.14573","repositories_listed":0,"syntology":null},{"url":null,"slug":"reexamining-racial-disparities-in-automatic","title":"Reexamining Racial Disparities in Automatic Speech Recognition Performance: The Role of Confounding by Provenance","date":"2024-07-19","arxiv_id":"2407.13982","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00004","title":"Handling Numeric Expressions in Automatic Speech Recognition","date":"2024-07-18","arxiv_id":"2408.00004","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-light-weight-and-efficient-punctuation-and","title":"A light-weight and efficient punctuation and word casing prediction model for on-device streaming ASR","date":"2024-07-18","arxiv_id":"2407.13142","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resourced-speech-recognition-for-iu-mien","title":"Low-Resourced Speech Recognition for Iu Mien Language via Weakly-Supervised Phoneme-based Multilingual Pre-training","date":"2024-07-18","arxiv_id":"2407.13292","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-asr-error-correction-with-conservative","title":"Robust ASR Error Correction with Conservative Data Filtering","date":"2024-07-18","arxiv_id":"2407.13300","repositories_listed":0,"syntology":null},{"url":null,"slug":"morphosyntactic-analysis-for-childes","title":"Morphosyntactic Analysis for CHILDES","date":"2024-07-17","arxiv_id":"2407.12389","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-binary-multiclass-paraphasia-detection","title":"Beyond Binary: Multiclass Paraphasia Detection with Generative Pretrained Transformers and End-to-End Models","date":"2024-07-16","arxiv_id":"2407.11345","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-voiceprivacy-2022-challenge-progress-and","title":"The VoicePrivacy 2022 Challenge: Progress and Perspectives in Voice Anonymisation","date":"2024-07-16","arxiv_id":"2407.11516","repositories_listed":0,"syntology":null},{"url":null,"slug":"leave-no-knowledge-behind-during-knowledge","title":"Leave No Knowledge Behind During Knowledge Distillation: Towards Practical and Effective Knowledge Distillation for Code-Switching ASR Using Realistic Data","date":"2024-07-15","arxiv_id":"2407.10603","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-neural-biasing-for-contextual","title":"Improving Neural Biasing for Contextual Speech Recognition by Early Context Injection and Text Perturbation","date":"2024-07-14","arxiv_id":"2407.10303","repositories_listed":0,"syntology":null},{"url":null,"slug":"hebdb-a-weakly-supervised-dataset-for-hebrew","title":"HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing","date":"2024-07-10","arxiv_id":"2407.07566","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-speech-unit-selection-for-textless","title":"Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation","date":"2024-07-08","arxiv_id":"2407.18332","repositories_listed":0,"syntology":null},{"url":null,"slug":"homogeneous-speaker-features-for-on-the-fly","title":"Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation","date":"2024-07-08","arxiv_id":"2407.06310","repositories_listed":0,"syntology":null},{"url":null,"slug":"learnervoice-a-dataset-of-non-native-english","title":"LearnerVoice: A Dataset of Non-Native English Learners' Spontaneous Speech","date":"2024-07-05","arxiv_id":"2407.04280","repositories_listed":0,"syntology":null},{"url":null,"slug":"romanization-encoding-for-multilingual-asr","title":"Romanization Encoding For Multilingual ASR","date":"2024-07-05","arxiv_id":"2407.04368","repositories_listed":0,"syntology":null},{"url":"/paper/seed-asr-understanding-diverse-speech-and","slug":"seed-asr-understanding-diverse-speech-and","title":"Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition","date":"2024-07-05","arxiv_id":"2407.04675","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-learning-for-code-switching","title":"Semi-supervised Learning for Code-Switching ASR with Large Language Model Filter","date":"2024-07-05","arxiv_id":"2407.04219","repositories_listed":0,"syntology":null},{"url":null,"slug":"speculative-speech-recognition-by-audio","title":"Speculative Speech Recognition by Audio-Prefixed Low-Rank Adaptation of Language Models","date":"2024-07-05","arxiv_id":"2407.04641","repositories_listed":0,"syntology":null},{"url":null,"slug":"xlsr-transducer-streaming-asr-for-self","title":"XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models","date":"2024-07-05","arxiv_id":"2407.04439","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-accented-speech-recognition-using","title":"Improving Accented Speech Recognition using Data Augmentation based on Unsupervised Text-to-Speech Synthesis","date":"2024-07-04","arxiv_id":"2407.04047","repositories_listed":0,"syntology":null},{"url":null,"slug":"codec-asr-training-performant-automatic","title":"Codec-ASR: Training Performant Automatic Speech Recognition Systems with Discrete Speech Representations","date":"2024-07-03","arxiv_id":"2407.03495","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-ustc-nercslip-systems-for-the-icmc-asr","title":"The USTC-NERCSLIP Systems for The ICMC-ASR Challenge","date":"2024-07-02","arxiv_id":"2407.02052","repositories_listed":0,"syntology":null},{"url":null,"slug":"error-correction-by-paying-attention-to-both","title":"Error Correction by Paying Attention to Both Acoustic and Confidence References for Automatic Speech Recognition","date":"2024-06-29","arxiv_id":"2407.12817","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-llms-for-rescoring-n-best-asr","title":"Applying LLMs for Rescoring N-best ASR Hypotheses of Casual Conversations: Effects of Domain Adaptation and Context Carry-over","date":"2024-06-27","arxiv_id":"2406.18972","repositories_listed":0,"syntology":null},{"url":null,"slug":"tradition-or-innovation-a-comparison-of","title":"Tradition or Innovation: A Comparison of Modern ASR Methods for Forced Alignment","date":"2024-06-27","arxiv_id":"2406.19363","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-speech-recognition-for-hindi","title":"Automatic Speech Recognition for Hindi","date":"2024-06-26","arxiv_id":"2406.18135","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-data-pruning-for-automatic-speech","title":"Dynamic Data Pruning for Automatic Speech Recognition","date":"2024-06-26","arxiv_id":"2406.18373","repositories_listed":0,"syntology":null},{"url":null,"slug":"msr-86k-an-evolving-multilingual-corpus-with","title":"MSR-86K: An Evolving, Multilingual Corpus with 86,300 Hours of Transcribed Audio for Speech Recognition Research","date":"2024-06-26","arxiv_id":"2406.18301","repositories_listed":0,"syntology":null},{"url":null,"slug":"sc-moe-switch-conformer-mixture-of-experts","title":"SC-MoE: Switch Conformer Mixture of Experts for Unified Streaming and Non-streaming Code-Switching ASR","date":"2024-06-26","arxiv_id":"2406.18021","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-editing-for-lifelong-training-of","title":"Sequential Editing for Lifelong Training of Speech Recognition Models","date":"2024-06-25","arxiv_id":"2406.17935","repositories_listed":0,"syntology":null},{"url":null,"slug":"blending-llms-into-cascaded-speech","title":"Blending LLMs into Cascaded Speech Translation: KIT's Offline Speech Translation System for IWSLT 2024","date":"2024-06-24","arxiv_id":"2406.16777","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextualized-end-to-end-automatic-speech","title":"Contextualized End-to-end Automatic Speech Recognition with Intermediate Biasing Loss","date":"2024-06-23","arxiv_id":"2406.16120","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoder-only-architecture-for-streaming-end","title":"Decoder-only Architecture for Streaming End-to-end Speech Recognition","date":"2024-06-23","arxiv_id":"2406.16107","repositories_listed":0,"syntology":null},{"url":null,"slug":"perception-of-phonological-assimilation-by","title":"Perception of Phonological Assimilation by Neural Speech Recognition Models","date":"2024-06-21","arxiv_id":"2406.15265","repositories_listed":0,"syntology":null},{"url":null,"slug":"pi-whisper-an-adaptive-and-incremental-asr","title":"PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices","date":"2024-06-21","arxiv_id":"2406.15668","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adapter-based-unified-model-for-multiple","title":"An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks","date":"2024-06-20","arxiv_id":"2406.14747","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligent-interface-enhancing-lecture","title":"Intelligent Interface: Enhancing Lecture Engagement with Didactic Activity Summaries","date":"2024-06-20","arxiv_id":"2406.14266","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-vs-sequential-speaker-role-detection","title":"Joint vs Sequential Speaker-Role Detection and Automatic Speech Recognition for Air-traffic Control","date":"2024-06-19","arxiv_id":"2406.13842","repositories_listed":0,"syntology":null},{"url":null,"slug":"manwav-the-first-manchu-asr-model","title":"ManWav: The First Manchu ASR Model","date":"2024-06-19","arxiv_id":"2406.13502","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-task-specific-subnetworks-in-multi","title":"Finding Task-specific Subnetworks in Multi-task Spoken Language Understanding Model","date":"2024-06-18","arxiv_id":"2406.12317","repositories_listed":0,"syntology":null},{"url":null,"slug":"performant-asr-models-for-medical-entities-in","title":"Performant ASR Models for Medical Entities in Accented Speech","date":"2024-06-18","arxiv_id":"2406.12387","repositories_listed":0,"syntology":null},{"url":null,"slug":"transcribe-align-and-segment-creating-speech","title":"Transcribe, Align and Segment: Creating speech datasets for low-resource languages","date":"2024-06-18","arxiv_id":"2406.12674","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-speech-recognition-for-biomedical","title":"Automatic Speech Recognition for Biomedical Data in Bengali Language","date":"2024-06-16","arxiv_id":"2406.12931","repositories_listed":0,"syntology":null},{"url":null,"slug":"costa-code-switched-speech-translation-using","title":"CoSTA: Code-Switched Speech Translation using Aligned Speech-Text Interleaving","date":"2024-06-16","arxiv_id":"2406.10993","repositories_listed":0,"syntology":null},{"url":null,"slug":"imperceptible-rhythm-backdoor-attacks","title":"Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition","date":"2024-06-16","arxiv_id":"2406.10932","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-dysfluency","title":"Large Language Models for Dysfluency Detection in Stuttered Speech","date":"2024-06-16","arxiv_id":"2406.11025","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-text-augmentation-approach-for","title":"An efficient text augmentation approach for contextualized Mandarin speech recognition","date":"2024-06-14","arxiv_id":"2406.09950","repositories_listed":0,"syntology":null},{"url":null,"slug":"inclusive-asr-for-disfluent-speech-cascaded","title":"Inclusive ASR for Disfluent Speech: Cascaded Large-Scale Self-Supervised Learning with Targeted Fine-Tuning and Data Augmentation","date":"2024-06-14","arxiv_id":"2406.10177","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-language-structures-through","title":"Learning Language Structures through Grounding","date":"2024-06-14","arxiv_id":"2406.09662","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-byte-level-representation-for-end","title":"Optimizing Byte-level Representation for End-to-end ASR","date":"2024-06-14","arxiv_id":"2406.09676","repositories_listed":0,"syntology":null},{"url":null,"slug":"roar-reinforcing-original-to-augmented-data","title":"ROAR: Reinforcing Original to Augmented Data Ratio Dynamics for Wav2Vec2.0 Based ASR","date":"2024-06-14","arxiv_id":"2406.09999","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-channel-multi-speaker-asr-using-target","title":"Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment","date":"2024-06-13","arxiv_id":"2406.09589","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-retrieval-for-large-language","title":"Multi-Modal Retrieval For Large Language Model Based Speech Recognition","date":"2024-06-13","arxiv_id":"2406.09618","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-second-displace-challenge-diarization-of","title":"The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments","date":"2024-06-13","arxiv_id":"2406.09494","repositories_listed":0,"syntology":null},{"url":null,"slug":"transcription-free-fine-tuning-of-speech","title":"Transcription-Free Fine-Tuning of Speech Separation Models for Noisy and Reverberant Multi-Speaker Automatic Speech Recognition","date":"2024-06-13","arxiv_id":"2406.08914","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-conditioned-phonemic-and-prosodic","title":"Audio-conditioned phonemic and prosodic annotation for building text-to-speech models from unlabeled speech data","date":"2024-06-12","arxiv_id":"2406.08111","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-pipeline-with-low-rank-adaptation-for","title":"Dual-Pipeline with Low-Rank Adaptation for New Language Integration in Multilingual ASR","date":"2024-06-12","arxiv_id":"2406.07842","repositories_listed":0,"syntology":null},{"url":null,"slug":"dualvc-3-leveraging-language-model-generated","title":"DualVC 3: Leveraging Language Model Generated Pseudo Context for End-to-end Low Latency Streaming Voice Conversion","date":"2024-06-12","arxiv_id":"2406.07846","repositories_listed":0,"syntology":null},{"url":null,"slug":"ml-superb-2-0-benchmarking-multilingual","title":"ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets","date":"2024-06-12","arxiv_id":"2406.08641","repositories_listed":0,"syntology":null},{"url":null,"slug":"prodeliberation-parallel-robust-deliberation","title":"PRoDeliberation: Parallel Robust Deliberation for End-to-End Spoken Language Understanding","date":"2024-06-12","arxiv_id":"2406.07823","repositories_listed":0,"syntology":null},{"url":null,"slug":"refining-self-supervised-learnt-speech","title":"Refining Self-Supervised Learnt Speech Representation using Brain Activations","date":"2024-06-12","arxiv_id":"2406.08266","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer-based-model-for-asr-n-best","title":"Transformer-based Model for ASR N-Best Rescoring and Rewriting","date":"2024-06-12","arxiv_id":"2406.08207","repositories_listed":0,"syntology":null},{"url":null,"slug":"as-70-a-mandarin-stuttered-speech-dataset-for","title":"AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection","date":"2024-06-11","arxiv_id":"2406.07256","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-context-biasing-for-ctc-and-transducer","title":"Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter","date":"2024-06-11","arxiv_id":"2406.07096","repositories_listed":0,"syntology":null},{"url":null,"slug":"reading-miscue-detection-in-primary-school","title":"Reading Miscue Detection in Primary School through Automatic Speech Recognition","date":"2024-06-11","arxiv_id":"2406.07060","repositories_listed":0,"syntology":null},{"url":null,"slug":"tag-and-correct-high-precision-post-editing","title":"Tag and correct: high precision post-editing approach to correction of speech recognition errors","date":"2024-06-11","arxiv_id":"2406.07589","repositories_listed":0,"syntology":null},{"url":null,"slug":"astra-aligning-speech-and-text","title":"ASTRA: Aligning Speech and Text Representations for Asr without Sampling","date":"2024-06-10","arxiv_id":"2406.06664","repositories_listed":0,"syntology":null},{"url":null,"slug":"ms-hubert-mitigating-pre-training-and","title":"MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations","date":"2024-06-09","arxiv_id":"2406.05661","repositories_listed":0,"syntology":null},{"url":null,"slug":"lora-whisper-parameter-efficient-and","title":"LoRA-Whisper: Parameter-Efficient and Extensible Multilingual ASR","date":"2024-06-07","arxiv_id":"2406.06619","repositories_listed":0,"syntology":null},{"url":null,"slug":"pitch-aware-rnn-t-for-mandarin-chinese","title":"Pitch-Aware RNN-T for Mandarin Chinese Mispronunciation Detection and Diagnosis","date":"2024-06-07","arxiv_id":"2406.04595","repositories_listed":0,"syntology":null},{"url":null,"slug":"flexible-multichannel-speech-enhancement-for","title":"Flexible Multichannel Speech Enhancement for Noise-Robust Frontend","date":"2024-06-06","arxiv_id":"2406.04552","repositories_listed":0,"syntology":null},{"url":null,"slug":"hypernetworks-for-personalizing-asr-to","title":"Hypernetworks for Personalizing ASR to Atypical Speech","date":"2024-06-06","arxiv_id":"2406.04240","repositories_listed":0,"syntology":null}],"record_sha256":"7b91519a78a061d69a278973ef5e477d3b75e54905ab28f412742fc941ae1020","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}