{"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-recognition/papers/60","list_of":"/task/speech-recognition","task":"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":60,"pages_in_order":65,"rows_per_page":100,"rows":[5901,6000],"of":6433,"counts":{"archive_papers_tagged":6433,"with_a_code_link":1373,"where_syntology_ran_a_sample":196,"not_listed_spam_title":0,"listed":6433,"listed_where_code_ran":196,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":162,"every_run_a_failure_of_syntologys_instrument":34,"listed_with_a_run_with_no_instrument_failure":162,"listed_every_run_a_failure_of_syntologys_instrument":34,"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-recognition","prev":"/task/speech-recognition/papers/59","next":"/task/speech-recognition/papers/61","papers":[{"url":null,"slug":"topic-identification-and-discovery-on-text","title":"Topic Identification and Discovery on Text and Speech","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"turn-taking-phenomena-in-incremental-dialogue","title":"Turn-taking phenomena in incremental dialogue systems","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"user-adaptive-restoration-for-incorrectly","title":"User Adaptive Restoration for Incorrectly-Segmented Utterances in Spoken Dialogue Systems","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"partitioning-large-scale-deep-belief-networks","title":"Partitioning Large Scale Deep Belief Networks Using Dropout","date":"2015-08-28","arxiv_id":"1508.07096","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-modelling-of-morphologically","title":"Probabilistic Modelling of Morphologically Rich Languages","date":"2015-08-18","arxiv_id":"1508.04271","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-and-accurate-recurrent-neural-network","title":"Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition","date":"2015-07-24","arxiv_id":"1507.06947","repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-segmental-cascades-for-feature","title":"Discriminative Segmental Cascades for Feature-Rich Phone Recognition","date":"2015-07-22","arxiv_id":"1507.06073","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-speech-recognition-using-consensus","title":"Robust speech recognition using consensus function based on multi-layer networks","date":"2015-07-22","arxiv_id":"1507.06023","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-normalisation-for-robust-speech","title":"Feature Normalisation for Robust Speech Recognition","date":"2015-07-14","arxiv_id":"1507.04019","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-lstm-based-dialog-state-tracker","title":"Incremental LSTM-based Dialog State Tracker","date":"2015-07-13","arxiv_id":"1507.03471","repositories_listed":0,"syntology":null},{"url":null,"slug":"describing-multimedia-content-using-attention","title":"Describing Multimedia Content using Attention-based Encoder--Decoder Networks","date":"2015-07-04","arxiv_id":"1507.01053","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-pilot-study-on-arabic-multi-genre-corpus","title":"A Pilot Study on Arabic Multi-Genre Corpus Diacritization","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"best-practices-for-crowdsourcing-dialectal","title":"Best Practices for Crowdsourcing Dialectal Arabic Speech Transcription","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"classifying-arab-names-geographically","title":"Classifying Arab Names Geographically","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"counting-what-counts-decompounding-for","title":"Counting What Counts: Decompounding for Keyphrase Extraction","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"driving-rover-with-segment-based-asr-quality","title":"Driving ROVER with Segment-based ASR Quality Estimation","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-disfluency-detection-with","title":"Efficient Disfluency Detection with Transition-based Parsing","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-incremental-dependency-parsing","title":"Generative Incremental Dependency Parsing with Neural Networks","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-reference-evaluation-for-dialectal","title":"Multi-Reference Evaluation for Dialectal Speech Recognition System: A Study for Egyptian ASR","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ncsu_sas_wookhee-a-deep-contextual-long-short","title":"NCSU\\_SAS\\_WOOKHEE: A Deep Contextual Long-Short Term Memory Model for Text Normalization","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-role-labeling-improves-incremental","title":"Semantic Role Labeling Improves Incremental Parsing","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sentence-selection-for-automatic-scoring-of","title":"Sentence selection for automatic scoring of Mandarin proficiency","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-fixed-size-ordinally-forgetting-encoding","title":"The Fixed-Size Ordinally-Forgetting Encoding Method for Neural Network Language Models","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"trans-dimensional-random-fields-for-language","title":"Trans-dimensional Random Fields for Language Modeling","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nonparametric-bayesian-double-articulation","title":"Nonparametric Bayesian Double Articulation Analyzer for Direct Language Acquisition from Continuous Speech Signals","date":"2015-06-22","arxiv_id":"1506.06646","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognize-foreign-low-frequency-words-with","title":"Recognize Foreign Low-Frequency Words with Similar Pairs","date":"2015-06-16","arxiv_id":"1506.04940","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-series-classification-using-the-hidden","title":"Time Series Classification using the Hidden-Unit Logistic Model","date":"2015-06-16","arxiv_id":"1506.05085","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-transfer-pre-training","title":"Knowledge Transfer Pre-training","date":"2015-06-07","arxiv_id":"1506.02256","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybridized-feature-extraction-and-acoustic","title":"Hybridized Feature Extraction and Acoustic Modelling Approach for Dysarthric Speech Recognition","date":"2015-06-06","arxiv_id":"1506.02170","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-structured-deep-neural-network-for","title":"Towards Structured Deep Neural Network for Automatic Speech Recognition","date":"2015-06-03","arxiv_id":"1506.01163","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-speech-rate-in-speech-recognition","title":"Learning Speech Rate in Speech Recognition","date":"2015-06-02","arxiv_id":"1506.00799","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-web-application-for-automated-dialect","title":"A Web Application for Automated Dialect Analysis","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"book-reviews-robots-that-talk-and-listen","title":"Book Reviews: Robots that Talk and Listen edited by Judith A. Markowitz","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cache-augmented-latent-topic-language-models","title":"Cache-Augmented Latent Topic Language Models for Speech Retrieval","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-open-source-annotators-for-entity","title":"Combining Open Source Annotators for Entity Linking through Weighted Voting","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"el92-entity-linking-combining-open-source","title":"EL92: Entity Linking Combining Open Source Annotators via Weighted Voting","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-semantic-frame-annotation","title":"Scaling Semantic Frame Annotation","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sopa-random-forests-regression-for-the","title":"SOPA: Random Forests Regression for the Semantic Textual Similarity task","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-text-normalization-using","title":"Unsupervised Text Normalization Using Distributed Representations of Words and Phrases","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"open-ended-intelligence-the-individuation-of","title":"Open Ended Intelligence: The individuation of Intelligent Agents","date":"2015-05-23","arxiv_id":"1505.06366","repositories_listed":0,"syntology":null},{"url":"/paper/the-ibm-2015-english-conversational-telephone","slug":"the-ibm-2015-english-conversational-telephone","title":"The IBM 2015 English Conversational Telephone Speech Recognition System","date":"2015-05-21","arxiv_id":"1505.05899","repositories_listed":0,"syntology":null},{"url":null,"slug":"recurrent-neural-network-training-with-dark","title":"Recurrent Neural Network Training with Dark Knowledge Transfer","date":"2015-05-18","arxiv_id":"1505.04630","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-selection-using-fishers-ratio","title":"Feature selection using Fisher's ratio technique for automatic speech recognition","date":"2015-05-13","arxiv_id":"1505.03239","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-neural-networks-with-bunches-of","title":"Improving neural networks with bunches of neurons modeled by Kumaraswamy units: Preliminary study","date":"2015-05-11","arxiv_id":"1505.02581","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-incremental-algorithm-for-transition-based","title":"An Incremental Algorithm for Transition-based CCG Parsing","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-performance-of-automatic-speech","title":"Assessing the Performance of Automatic Speech Recognition Systems When Used by Native and Non-Native Speakers of Three Major Languages in Dictation Workflows","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-and-continuous-representations","title":"Deep Learning and Continuous Representations for Natural Language Processing","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-linking-for-spoken-language","title":"Entity Linking for Spoken Language","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"lexicon-free-conversational-speech","title":"Lexicon-Free Conversational Speech Recognition with Neural Networks","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multitask-learning-for-adaptive-quality","title":"Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-parsing-of-speech-using-grammars","title":"Semantic parsing of speech using grammars learned with weak supervision","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sentence-compression-for-automatic-subtitling","title":"Sentence Compression For Automatic Subtitling","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sentence-segmentation-of-aphasic-speech","title":"Sentence segmentation of aphasic speech","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"smart-computer-aided-translation-environment","title":"Smart Computer Aided Translation Environment - SCATE","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unediting-detecting-disfluencies-without","title":"Unediting: Detecting Disfluencies Without Careful Transcripts","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-sub-word-n-gram-models-for-dealing-with","title":"Using sub-word n-gram models for dealing with OOV in large vocabulary speech recognition for Latvian","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"when-and-why-are-log-linear-models-self","title":"When and why are log-linear models self-normalizing?","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-probabilistic-framework-for-representing","title":"A Probabilistic Framework for Representing Dialog Systems and Entropy-Based Dialog Management through Dynamic Stochastic State Evolution","date":"2015-04-27","arxiv_id":"1504.07182","repositories_listed":0,"syntology":null},{"url":"/paper/deep-recurrent-neural-networks-for-acoustic","slug":"deep-recurrent-neural-networks-for-acoustic","title":"Deep Recurrent Neural Networks for Acoustic Modelling","date":"2015-04-07","arxiv_id":"1504.01482","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferring-knowledge-from-a-rnn-to-a-dnn","title":"Transferring Knowledge from a RNN to a DNN","date":"2015-04-07","arxiv_id":"1504.01483","repositories_listed":0,"syntology":null},{"url":null,"slug":"voice-based-self-help-system-user-experience","title":"Voice based self help System: User Experience Vs Accuracy","date":"2015-04-07","arxiv_id":"1504.01496","repositories_listed":0,"syntology":null},{"url":null,"slug":"gibbs-sampling-with-low-power-spiking-digital","title":"Gibbs Sampling with Low-Power Spiking Digital Neurons","date":"2015-03-26","arxiv_id":"1503.07793","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-based-action-recognition-using-rate","title":"Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories","date":"2015-03-23","arxiv_id":"1503.06699","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-short-term-memory-over-tree-structures","title":"Long Short-Term Memory Over Tree Structures","date":"2015-03-16","arxiv_id":"1503.04881","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-state-conditional-observation","title":"Modeling State-Conditional Observation Distribution using Weighted Stereo Samples for Factorial Speech Processing Models","date":"2015-03-09","arxiv_id":"1503.02578","repositories_listed":0,"syntology":null},{"url":null,"slug":"maximum-a-posteriori-adaptation-of-network","title":"Maximum a Posteriori Adaptation of Network Parameters in Deep Models","date":"2015-03-06","arxiv_id":"1503.02108","repositories_listed":0,"syntology":null},{"url":null,"slug":"f0-modeling-in-hmm-based-speech-synthesis","title":"F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network","date":"2015-02-18","arxiv_id":"1502.05213","repositories_listed":0,"syntology":null},{"url":"/paper/hybrid-orthogonal-projection-and-estimation","slug":"hybrid-orthogonal-projection-and-estimation","title":"Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks","date":"2015-02-03","arxiv_id":"1502.00702","repositories_listed":0,"syntology":null},{"url":null,"slug":"belief-hidden-markov-model-for-speech","title":"Belief Hidden Markov Model for speech recognition","date":"2015-01-22","arxiv_id":"1501.05530","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-multimodal-learning-for-audio-visual","title":"Deep Multimodal Learning for Audio-Visual Speech Recognition","date":"2015-01-22","arxiv_id":"1501.05396","repositories_listed":0,"syntology":null},{"url":null,"slug":"phrase-based-language-model-for-statistical","title":"Phrase Based Language Model for Statistical Machine Translation: Empirical Study","date":"2015-01-21","arxiv_id":"1501.05203","repositories_listed":0,"syntology":null},{"url":null,"slug":"phrase-based-language-model-for-statistical-1","title":"Phrase Based Language Model For Statistical Machine Translation","date":"2015-01-18","arxiv_id":"1501.04324","repositories_listed":0,"syntology":null},{"url":null,"slug":"preserving-trees-in-minimal-automata","title":"Preserving Trees in Minimal Automata","date":"2015-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-lexicon-discovery-from-acoustic","title":"Unsupervised Lexicon Discovery from Acoustic Input","date":"2015-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-simple-and-accurate-handwritten-digit","title":"Fast, simple and accurate handwritten digit classification by training shallow neural network classifiers with the 'extreme learning machine' algorithm","date":"2014-12-29","arxiv_id":"1412.8307","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-linearly-separable-features-for","title":"Learning linearly separable features for speech recognition using convolutional neural networks","date":"2014-12-22","arxiv_id":"1412.7110","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-adaptation-strategies-for-neural","title":"Incremental Adaptation Strategies for Neural Network Language Models","date":"2014-12-20","arxiv_id":"1412.6650","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-broadcast-news-corpus-for-evaluation-and","title":"A Broadcast News Corpus for Evaluation and Tuning of German LVCSR Systems","date":"2014-12-15","arxiv_id":"1412.4616","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-continuous-speech-recognition","title":"End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results","date":"2014-12-04","arxiv_id":"1412.1602","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-concept-information-for-mandarin","title":"使用概念資訊於中文大詞彙連續語音辨識之研究 (Exploring Concept Information for Mandarin Large Vocabulary Continuous Speech Recognition) [In Chinese]","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hinma-distributed-morphology-based-hindi","title":"HinMA: Distributed Morphology based Hindi Morphological Analyzer","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-term-prediction-using-deep-belief","title":"Retrieval Term Prediction Using Deep Belief Networks","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"use-of-gpu-and-feature-reduction-for-fast","title":"Use of GPU and Feature Reduction for Fast Query-by-Example Spoken Term Detection","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-tone-information-in-thai-spelling","title":"Using Tone Information in Thai Spelling Speech Recognition","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":"zero-shot-learning-of-language-models-for","title":"Zero-Shot Learning of Language Models for Describing Human Actions Based on Semantic Compositionality of Actions","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-scale-up-kernel-methods-to-be-as-good","title":"How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets","date":"2014-11-14","arxiv_id":"1411.4000","repositories_listed":0,"syntology":null},{"url":null,"slug":"tied-probabilistic-linear-discriminant","title":"Tied Probabilistic Linear Discriminant Analysis for Speech Recognition","date":"2014-11-04","arxiv_id":"1411.0895","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-effect-of-dependency-representation","title":"The Effect of Dependency Representation Scheme on Syntactic Language Modelling","date":"2014-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mobility-enhancement-for-elderly","title":"Mobility Enhancement for Elderly","date":"2014-10-21","arxiv_id":"1410.5600","repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-long-short-term-memory-based","title":"Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition","date":"2014-10-16","arxiv_id":"1410.4281","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-diffuseness-features-for-dnn-based","title":"Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments","date":"2014-10-09","arxiv_id":"1410.2479","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-i-vector-based-approach-to-compact-multi","title":"An I-vector Based Approach to Compact Multi-Granularity Topic Spaces Representation of Textual Documents","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-punctuation-and-disfluency","title":"Combining Punctuation and Disfluency Prediction: An Empirical Study","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploration-of-the-impact-of-maximum-entropy","title":"Exploration of the Impact of Maximum Entropy in Recurrent Neural Network Language Models for Code-Switching Speech","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-novel-sentence-modeling","title":"探究新穎語句模型化技術於節錄式語音摘要 (Investigating Novel Sentence Modeling Techniques for Extractive Speech Summarization) [In Chinese]","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-identification-in-code-switching","title":"Language Identification in Code-Switching Scenario","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-modeling-with-functional-head","title":"Language Modeling with Functional Head Constraint for Code Switching Speech Recognition","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"large-scale-reordering-model-for-statistical","title":"Large-scale Reordering Model for Statistical Machine Translation using Dual Multinomial Logistic Regression","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-phrase-representations-using-rnn-1","title":"Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"93700c3be58f3a36e43df126ede88ae1800f15d62e4ae42728216ccacfd316dd","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}