{"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/speech-enhancement/papers/10","list_of":"/task/speech-enhancement","task":"Speech Enhancement","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":10,"pages_in_order":10,"rows_per_page":100,"rows":[901,982],"of":982,"counts":{"archive_papers_tagged":982,"with_a_code_link":280,"where_syntology_ran_a_sample":54,"not_listed_spam_title":0,"listed":982,"listed_where_code_ran":54,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":45,"every_run_a_failure_of_syntologys_instrument":9,"listed_with_a_run_with_no_instrument_failure":45,"listed_every_run_a_failure_of_syntologys_instrument":9,"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/speech-enhancement","prev":"/task/speech-enhancement/papers/9","next":null,"papers":[{"url":null,"slug":"semi-supervised-multichannel-speech","title":"Semi-supervised multichannel speech enhancement with variational autoencoders and non-negative matrix factorization","date":"2018-11-16","arxiv_id":"1811.06713","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-recurrences-in-time-and-frequency","title":"Using recurrences in time and frequency within U-net architecture for speech enhancement","date":"2018-11-16","arxiv_id":"1811.06805","repositories_listed":0,"syntology":null},{"url":null,"slug":"effects-of-lombard-reflex-on-the-performance","title":"Effects of Lombard Reflex on the Performance of Deep-Learning-Based Audio-Visual Speech Enhancement Systems","date":"2018-11-15","arxiv_id":"1811.06250","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-training-targets-and-objective-functions","title":"On Training Targets and Objective Functions for Deep-Learning-Based Audio-Visual Speech Enhancement","date":"2018-11-15","arxiv_id":"1811.06234","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-based-speech","title":"Reinforcement Learning Based Speech Enhancement for Robust Speech Recognition","date":"2018-11-10","arxiv_id":"1811.04224","repositories_listed":0,"syntology":null},{"url":null,"slug":"kernel-machines-beat-deep-neural-networks-on","title":"Kernel Machines Beat Deep Neural Networks on Mask-based Single-channel Speech Enhancement","date":"2018-11-06","arxiv_id":"1811.02095","repositories_listed":0,"syntology":null},{"url":null,"slug":"convs2s-vc-fully-convolutional-sequence-to","title":"ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion","date":"2018-11-05","arxiv_id":"1811.01609","repositories_listed":0,"syntology":null},{"url":null,"slug":"trainable-adaptive-window-switching-for","title":"Trainable Adaptive Window Switching for Speech Enhancement","date":"2018-11-05","arxiv_id":"1811.02438","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-speech-enhancement-in-unseen","title":"Scaling Speech Enhancement in Unseen Environments with Noise Embeddings","date":"2018-10-26","arxiv_id":"1810.12757","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-speech-enhancement-with-the-wave-u-1","title":"Improved Speech Enhancement with the Wave-U-Net","date":"2018-10-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-domain-processing-via-hybrid-denoising-1","title":"Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement","date":"2018-10-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-speech-command-recognition-using-label","title":"ROBUST SPEECH COMMAND RECOGNITION USING LABEL-DRIVEN TIME-FREQUENCY MASKING","date":"2018-10-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"phasebook-and-friends-leveraging-discrete","title":"Phasebook and Friends: Leveraging Discrete Representations for Source Separation","date":"2018-10-02","arxiv_id":"1810.01395","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-four-metaheuristic-applications-to-speech","title":"On Four Metaheuristic Applications to Speech Enhancement---Implementing Optimization Algorithms with MATLAB R2018a","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"new-insights-on-the-optimality-of","title":"New insights on the optimality of parameterized wiener filters for speech enhancement applications","date":"2018-09-19","arxiv_id":"1809.07384","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-feature-mapping-for-speech","title":"Adversarial Feature-Mapping for Speech Enhancement","date":"2018-09-06","arxiv_id":"1809.02251","repositories_listed":0,"syntology":null},{"url":null,"slug":"cycle-consistent-speech-enhancement","title":"Cycle-Consistent Speech Enhancement","date":"2018-09-06","arxiv_id":"1809.02253","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextual-audio-visual-switching-for-speech","title":"Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments","date":"2018-08-28","arxiv_id":"1808.09825","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-on-speech-enhancement-using-exponent","title":"A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)","date":"2018-08-17","arxiv_id":"1808.06474","repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-net-an-end-to-end-non-intrusive","title":"Quality-Net: An End-to-End Non-intrusive Speech Quality Assessment Model based on BLSTM","date":"2018-08-16","arxiv_id":"1808.05344","repositories_listed":0,"syntology":null},{"url":null,"slug":"lip-reading-driven-deep-learning-approach-for","title":"Lip-Reading Driven Deep Learning Approach for Speech Enhancement","date":"2018-07-31","arxiv_id":"1808.00046","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fully-convolutional-neural-network-approach","title":"A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement","date":"2018-07-20","arxiv_id":"1807.07959","repositories_listed":0,"syntology":null},{"url":null,"slug":"relative-transfer-function-estimation","title":"Relative Transfer Function Estimation Exploiting Spatially Separated Microphones in a Diffuse Noise Field","date":"2018-07-12","arxiv_id":"1805.10333","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-of-enhancement-augmentation-and","title":"A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition","date":"2018-06-13","arxiv_id":"1806.04841","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-noise-robustness-of-acoustic-model","title":"Boosting Noise Robustness of Acoustic Model via Deep Adversarial Training","date":"2018-05-02","arxiv_id":"1805.01357","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-recurrent-neural-networks-for-5","title":"Convolutional-Recurrent Neural Networks for Speech Enhancement","date":"2018-05-02","arxiv_id":"1805.00579","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-progresses-in-deep-learning-based","title":"Recent Progresses in Deep Learning based Acoustic Models (Updated)","date":"2018-04-25","arxiv_id":"1804.09298","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-conversation-deep-audio-visual-speech","title":"The Conversation: Deep Audio-Visual Speech Enhancement","date":"2018-04-11","arxiv_id":"1804.04121","repositories_listed":0,"syntology":null},{"url":"/paper/the-fifth-chime-speech-separation-and","slug":"the-fifth-chime-speech-separation-and","title":"The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines","date":"2018-03-28","arxiv_id":"1803.10609","repositories_listed":0,"syntology":null},{"url":"/paper/building-state-of-the-art-distant-speech","slug":"building-state-of-the-art-distant-speech","title":"Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline","date":"2018-03-27","arxiv_id":"1803.10109","repositories_listed":0,"syntology":null},{"url":null,"slug":"student-teacher-learning-for-blstm-mask-based","title":"Student-Teacher Learning for BLSTM Mask-based Speech Enhancement","date":"2018-03-27","arxiv_id":"1803.10013","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectral-feature-mapping-with-mimic-loss-for","title":"Spectral feature mapping with mimic loss for robust speech recognition","date":"2018-03-26","arxiv_id":"1803.09816","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-we-steal-your-vocal-identity-from-the","title":"Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data","date":"2018-03-02","arxiv_id":"1803.00860","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-enhancement-in-adverse-environments","title":"Speech Enhancement in Adverse Environments Based on Non-stationary Noise-driven Spectral Subtraction and SNR-dependent Phase Compensation","date":"2018-02-19","arxiv_id":"1803.00396","repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-convolutional-recurrent-networks","title":"Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy","date":"2018-02-16","arxiv_id":"1802.05874","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-speech-beamforming","title":"Deep Learning Based Speech Beamforming","date":"2018-02-15","arxiv_id":"1802.05383","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancement-of-noisy-speech-exploiting-an","title":"Enhancement of Noisy Speech Exploiting an Exponential Model Based Threshold and a Custom Thresholding Function in Perceptual Wavelet Packet Domain","date":"2018-02-15","arxiv_id":"1802.05962","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancement-of-noisy-speech-with-low-speech","title":"Enhancement of Noisy Speech with Low Speech Distortion Based on Probabilistic Geometric Spectral Subtraction","date":"2018-02-13","arxiv_id":"1802.05125","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-sparse-adversarial-dictionaries-for","title":"Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification","date":"2017-12-02","arxiv_id":"1712.00640","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-to-adapt-speech","title":"Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality","date":"2017-11-29","arxiv_id":"1711.10791","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-speech-enhancement","title":"Visual Speech Enhancement","date":"2017-11-23","arxiv_id":"1711.08789","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-speech-enhancement-with-generative","title":"Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition","date":"2017-11-15","arxiv_id":"1711.05747","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-e-e-a1e-c-ea14eaaeaac-c14a","title":"多樣訊雜比之訓練語料於降噪自動編碼器其語音強化功能之初步研究 (A Preliminary Study of Various SNR-level Training Data in the Denoising Auto-encoder (DAE) Technique for Speech Enhancement) [In Chinese]","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"aeecoaocaoeae3aa14c3ca12c-eae-development-of","title":"以軟體為基礎建構語音增強系統使用者介面 (Development of a software-based User-Interface of Speech Enhancement System) [In Chinese]","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-speech-enhancement-based-on","title":"Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization","date":"2017-10-31","arxiv_id":"1710.11439","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonnegative-hmm-for-babble-noise-derived-from","title":"Nonnegative HMM for Babble Noise Derived from Speech HMM: Application to Speech Enhancement","date":"2017-09-16","arxiv_id":"1709.05559","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-waveform-utterance-enhancement-for","title":"End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks","date":"2017-09-12","arxiv_id":"1709.03658","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-generative-adversarial-networks-1","title":"Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification","date":"2017-09-06","arxiv_id":"1709.01703","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-visual-speech-enhancement-based-on","title":"Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks","date":"2017-09-01","arxiv_id":"1709.00944","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-speech-separation-based-on-deep","title":"Supervised Speech Separation Based on Deep Learning: An Overview","date":"2017-08-24","arxiv_id":"1708.07524","repositories_listed":0,"syntology":null},{"url":null,"slug":"perceptual-audio-loss-function-for-deep","title":"Perceptual audio loss function for deep learning","date":"2017-08-20","arxiv_id":"1708.05987","repositories_listed":0,"syntology":null},{"url":null,"slug":"face-recognition-with-machine-learning-in","title":"Face Recognition with Machine Learning in OpenCV_ Fusion of the results with the Localization Data of an Acoustic Camera for Speaker Identification","date":"2017-07-04","arxiv_id":"1707.00835","repositories_listed":0,"syntology":null},{"url":null,"slug":"hidden-markov-model-based-speech-enhancement","title":"Hidden-Markov-Model Based Speech Enhancement","date":"2017-07-04","arxiv_id":"1707.01090","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaborative-deep-learning-for-speech","title":"Collaborative Deep Learning for Speech Enhancement: A Run-Time Model Selection Method Using Autoencoders","date":"2017-05-29","arxiv_id":"1705.10385","repositories_listed":0,"syntology":null},{"url":null,"slug":"complex-spectrogram-enhancement-by","title":"Complex spectrogram enhancement by convolutional neural network with multi-metrics learning","date":"2017-04-27","arxiv_id":"1704.08504","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-visual-speech-enhancement-using","title":"Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks","date":"2017-03-30","arxiv_id":"1703.10893","repositories_listed":0,"syntology":null},{"url":null,"slug":"batch-normalized-joint-training-for-dnn-based","title":"Batch-normalized joint training for DNN-based distant speech recognition","date":"2017-03-24","arxiv_id":"1703.08471","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-network-of-deep-neural-networks-for-distant","title":"A network of deep neural networks for distant speech recognition","date":"2017-03-23","arxiv_id":"1703.08002","repositories_listed":0,"syntology":null},{"url":null,"slug":"multichannel-end-to-end-speech-recognition","title":"Multichannel End-to-end Speech Recognition","date":"2017-03-14","arxiv_id":"1703.04783","repositories_listed":0,"syntology":null},{"url":null,"slug":"raw-waveform-based-speech-enhancement-by","title":"Raw Waveform-based Speech Enhancement by Fully Convolutional Networks","date":"2017-03-07","arxiv_id":"1703.02205","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-of-voice-conversion-techniques","title":"Robustness of Voice Conversion Techniques Under Mismatched Conditions","date":"2016-12-22","arxiv_id":"1612.07523","repositories_listed":0,"syntology":null},{"url":null,"slug":"dictionary-update-for-nmf-based-voice","title":"Dictionary Update for NMF-based Voice Conversion Using an Encoder-Decoder Network","date":"2016-10-13","arxiv_id":"1610.03988","repositories_listed":0,"syntology":null},{"url":null,"slug":"ee2-ceae314eae3eaee-ea14aa1c-ca-study-of","title":"非負矩陣分解法於語音調變頻譜強化之研究(A study of enhancing the modulation spectrum of speech signals via nonnegative matrix factorization)[In Chinese]","date":"2016-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-curriculum-learning-method-for-improved","title":"A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition","date":"2016-06-22","arxiv_id":"1606.06864","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-hybrid-deep-neural-network-for","title":"Multi-Modal Hybrid Deep Neural Network for Speech Enhancement","date":"2016-06-15","arxiv_id":"1606.04750","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-channel-speech-enhancement-using","title":"Single Channel Speech Enhancement Using Outlier Detection","date":"2016-05-04","arxiv_id":"1605.01329","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-recording-device-identification-based","title":"Audio Recording Device Identification Based on Deep Learning","date":"2016-02-18","arxiv_id":"1602.05682","repositories_listed":0,"syntology":null},{"url":null,"slug":"recurrent-models-for-auditory-attention-in","title":"Recurrent Models for Auditory Attention in Multi-Microphone Distance Speech Recognition","date":"2015-11-19","arxiv_id":"1511.06407","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-speech-enhancement-system-based-on","title":"語音增強基於小腦模型控制器(A Speech Enhancement System Based on Cerebellar Model Articulation Controller) [In Chinese]","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"noise-robust-asr-for-the-third-chime","title":"Noise-Robust ASR for the third 'CHiME' Challenge Exploiting Time-Frequency Masking based Multi-Channel Speech Enhancement and Recurrent Neural Network","date":"2015-09-24","arxiv_id":"1509.07211","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancement-and-recognition-of-reverberant","title":"Enhancement and Recognition of Reverberant and Noisy Speech by Extending Its Coherence","date":"2015-09-02","arxiv_id":"1509.00533","repositories_listed":0,"syntology":null},{"url":null,"slug":"vowel-enhancement-in-early-stage-spanish","title":"Vowel Enhancement in Early Stage Spanish Esophageal Speech Using Natural Glottal Flow Pulse and Vocal Tract Frequency Warping","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"low-rank-time-frequency-synthesis","title":"Low-Rank Time-Frequency Synthesis","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"voice-activity-detection-using-temporal","title":"Voice Activity Detection using Temporal Characteristics of Autocorrelation Lag and Maximum Spectral Amplitude in Sub-bands","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-unfolding-model-based-inspiration-of","title":"Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures","date":"2014-09-09","arxiv_id":"1409.2574","repositories_listed":0,"syntology":null},{"url":null,"slug":"design-and-optimization-of-a-speech","title":"Design and Optimization of a Speech Recognition Front-End for Distant-Talking Control of a Music Playback Device","date":"2014-05-05","arxiv_id":"1405.1379","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-negative-matrix-factorization-with-linear","title":"Non-negative Matrix Factorization with Linear Constraints for Single-Channel Speech Enhancement","date":"2013-09-24","arxiv_id":"1309.6047","repositories_listed":0,"syntology":null},{"url":null,"slug":"group-sparse-signal-denoising-non-convex","title":"Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization","date":"2013-08-23","arxiv_id":"1308.5038","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-enhancement-using-pitch-detection","title":"Speech Enhancement Using Pitch Detection Approach For Noisy Environment","date":"2013-05-09","arxiv_id":"1305.2352","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-enhancement-modeling-towards-robust","title":"Speech Enhancement Modeling Towards Robust Speech Recognition System","date":"2013-05-07","arxiv_id":"1305.1426","repositories_listed":0,"syntology":null},{"url":null,"slug":"translation-invariant-shrinkagethresholding","title":"Translation-Invariant Shrinkage/Thresholding of Group Sparse Signals","date":"2013-03-29","arxiv_id":"1304.0035","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligibility-assessment-in-forensic","title":"Intelligibility assessment in forensic applications","date":"2012-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"dd9513f420a140f22c378a44377754cc2287e8c474dd9fea3b214b5b84d48518","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}