{"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-1/papers/55","list_of":"/task/speech-recognition-1","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":55,"pages_in_order":58,"rows_per_page":100,"rows":[5401,5500],"of":5715,"counts":{"archive_papers_tagged":5715,"with_a_code_link":1277,"where_syntology_ran_a_sample":162,"not_listed_spam_title":0,"listed":5715,"listed_where_code_ran":162,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":134,"every_run_a_failure_of_syntologys_instrument":28,"listed_with_a_run_with_no_instrument_failure":134,"listed_every_run_a_failure_of_syntologys_instrument":28,"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-1","prev":"/task/speech-recognition-1/papers/54","next":"/task/speech-recognition-1/papers/56","papers":[{"url":null,"slug":"babler-data-collection-from-the-web-to","title":"Babler - Data Collection from the Web to Support Speech Recognition and Keyword Search","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"blind-phoneme-segmentation-with-temporal","title":"Blind phoneme segmentation with temporal prediction errors","date":"2016-08-01","arxiv_id":"1608.00508","repositories_listed":0,"syntology":null},{"url":null,"slug":"transcrater-a-tool-for-automatic-speech","title":"TranscRater: a Tool for Automatic Speech Recognition Quality Estimation","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"piecewise-convexity-of-artificial-neural","title":"Piecewise convexity of artificial neural networks","date":"2016-07-17","arxiv_id":"1607.04917","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-efficient-representation-and-execution","title":"On the efficient representation and execution of deep acoustic models","date":"2016-07-15","arxiv_id":"1607.04683","repositories_listed":0,"syntology":null},{"url":null,"slug":"intra-layer-nonuniform-quantization-for-deep","title":"Intra-layer Nonuniform Quantization for Deep Convolutional Neural Network","date":"2016-07-10","arxiv_id":"1607.02720","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequence-training-and-adaptation-of-highway","title":"Sequence Training and Adaptation of Highway Deep Neural Networks","date":"2016-07-07","arxiv_id":"1607.01963","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimation-de-la-qualit-e-d-un-syst-eme-de","title":"Estimation de la qualit\\'e d'un syst\\`eme de reconnaissance de la parole pour une t\\^ache de compr\\'ehension (Quality estimation of a Speech Recognition System for a Spoken Language Understanding task)","date":"2016-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"from-human-language-technology-to-human","title":"From Human Language Technology to Human Language Science","date":"2016-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"moving-toward-high-precision-dynamical","title":"Moving Toward High Precision Dynamical Modelling in Hidden Markov Models","date":"2016-07-01","arxiv_id":"1607.00359","repositories_listed":0,"syntology":null},{"url":null,"slug":"generation-and-pruning-of-pronunciation","title":"Generation and Pruning of Pronunciation Variants to Improve ASR Accuracy","date":"2016-06-28","arxiv_id":"1606.08821","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-ldcrf-model-on-unsegmented-sequences","title":"Training LDCRF model on unsegmented sequences using Connectionist Temporal Classification","date":"2016-06-26","arxiv_id":"1606.08051","repositories_listed":0,"syntology":null},{"url":null,"slug":"nn-grams-unifying-neural-network-and-n-gram","title":"NN-grams: Unifying neural network and n-gram language models for Speech Recognition","date":"2016-06-23","arxiv_id":"1606.07470","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-study-of-deep-bidirectional","title":"A Comprehensive Study of Deep Bidirectional LSTM RNNs for Acoustic Modeling in Speech Recognition","date":"2016-06-22","arxiv_id":"1606.06871","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":"a-nonparametric-bayesian-approach-for-spoken","title":"A Nonparametric Bayesian Approach for Spoken Term detection by Example Query","date":"2016-06-20","arxiv_id":"1606.05967","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-based-manifold-regularized-deep-neural","title":"Graph based manifold regularized deep neural networks for automatic speech recognition","date":"2016-06-19","arxiv_id":"1606.05925","repositories_listed":0,"syntology":null},{"url":null,"slug":"increasing-the-interpretability-of-recurrent","title":"Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models","date":"2016-06-16","arxiv_id":"1606.05320","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectral-decomposition-method-of-dialog-state","title":"Spectral decomposition method of dialog state tracking via collective matrix factorization","date":"2016-06-16","arxiv_id":"1606.05286","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-pronunciation-generation-by","title":"Automatic Pronunciation Generation by Utilizing a Semi-supervised Deep Neural Networks","date":"2016-06-15","arxiv_id":"1606.05007","repositories_listed":0,"syntology":null},{"url":null,"slug":"calibration-of-phone-likelihoods-in-automatic","title":"Calibration of Phone Likelihoods in Automatic Speech Recognition","date":"2016-06-14","arxiv_id":"1606.04317","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-variance-and-performance-evaluation","title":"Training variance and performance evaluation of neural networks in speech","date":"2016-06-14","arxiv_id":"1606.04521","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialog-state-tracking-a-machine-reading","title":"Dialog state tracking, a machine reading approach using Memory Network","date":"2016-06-13","arxiv_id":"1606.04052","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-spiking-network-that-learns-to-extract","title":"A Spiking Network that Learns to Extract Spike Signatures from Speech Signals","date":"2016-06-02","arxiv_id":"1606.00802","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-hessian-free-optimization-for","title":"Distributed Hessian-Free Optimization for Deep Neural Network","date":"2016-06-02","arxiv_id":"1606.00511","repositories_listed":0,"syntology":null},{"url":null,"slug":"temporal-multimodal-learning-in-audiovisual","title":"Temporal Multimodal Learning in Audiovisual Speech Recognition","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"design-and-development-a-childrens-speech","title":"Design and development a children's speech database","date":"2016-05-25","arxiv_id":"1605.07735","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-model-architecture-for-a-childrens-speech","title":"On model architecture for a children's speech recognition interactive dialog system","date":"2016-05-25","arxiv_id":"1605.07733","repositories_listed":0,"syntology":null},{"url":null,"slug":"contour-based-3d-tongue-motion-visualization","title":"Contour-based 3d tongue motion visualization using ultrasound image sequences","date":"2016-05-19","arxiv_id":"1605.05967","repositories_listed":0,"syntology":null},{"url":null,"slug":"noisy-parallel-approximate-decoding-for","title":"Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model","date":"2016-05-12","arxiv_id":"1605.03835","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-ibm-speaker-recognition-system-recent","title":"The IBM Speaker Recognition System: Recent Advances and Error Analysis","date":"2016-05-05","arxiv_id":"1605.01635","repositories_listed":0,"syntology":null},{"url":null,"slug":"theanolm-an-extensible-toolkit-for-neural","title":"TheanoLM - An Extensible Toolkit for Neural Network Language Modeling","date":"2016-05-03","arxiv_id":"1605.00942","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-analysis-of-crowdsourced","title":"A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-corpus-of-read-and-spontaneous-upper-saxon","title":"A Corpus of Read and Spontaneous Upper Saxon German Speech for ASR Evaluation","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-extension-of-the-slovak-broadcast-news","title":"An Extension of the Slovak Broadcast News Corpus based on Semi-Automatic Annotation","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"challenges-and-solutions-for-consistent","title":"Challenges and Solutions for Consistent Annotation of Vietnamese Treebank","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"designing-a-speech-corpus-for-the-development","title":"Designing a Speech Corpus for the Development and Evaluation of Dictation Systems in Latvian","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"endangered-language-documentation","title":"Endangered Language Documentation: Bootstrapping a Chatino Speech Corpus, Forced Aligner, ASR","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-corilga-introducing-the-automatic","title":"Enhanced CORILGA: Introducing the Automatic Phonetic Alignment Tool for Continuous Speech","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-weighted-language-lexicons-from","title":"Extracting Weighted Language Lexicons from Wikipedia","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"falling-silent-lost-for-words-tracing","title":"Falling silent, lost for words ... Tracing personal involvement in interviews with Dutch war veterans","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-task-pertinent-sorted-error-lists","title":"Generating Task-Pertinent sorted Error Lists for Speech Recognition","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-diachronic-text-corpora-affect-context","title":"How Diachronic Text Corpora Affect Context based Retrieval of OOV Proper Names for Audio News","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"joining-in-type-humanoid-robot-assisted","title":"Joining-in-type Humanoid Robot Assisted Language Learning System","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"operational-assessment-of-keyword-search-on","title":"Operational Assessment of Keyword Search on Oral History","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-corpus-spoken-by-young-old-old-old-and","title":"Speech Corpus Spoken by Young-old, Old-old and Oldest-old Japanese","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-dirha-portuguese-corpus-a-comparison-of","title":"The DIRHA Portuguese Corpus: A Comparison of Home Automation Command Detection and Recognition in Simulated and Real Data.","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-ilmt-s2s-corpus-a-a-multimodal","title":"The ILMT-s2s Corpus ― A Multimodal Interlingual Map Task Corpus","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-si-tedx-um-speech-database-a-new","title":"The SI TEDx-UM speech database: a new Slovenian Spoken Language Resource","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automatic-transcription-of-ilse-a-an","title":"Towards Automatic Transcription of ILSE ― an Interdisciplinary Longitudinal Study of Adult Development and Aging","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-the-ted-talks-to-evaluate-spoken-post","title":"Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/the-ibm-2016-english-conversational-telephone","slug":"the-ibm-2016-english-conversational-telephone","title":"The IBM 2016 English Conversational Telephone Speech Recognition System","date":"2016-04-27","arxiv_id":"1604.08242","repositories_listed":0,"syntology":null},{"url":null,"slug":"speaker-cluster-based-speaker-adaptive","title":"Speaker Cluster-Based Speaker Adaptive Training for Deep Neural Network Acoustic Modeling","date":"2016-04-20","arxiv_id":"1604.06113","repositories_listed":0,"syntology":null},{"url":null,"slug":"composition-of-deep-and-spiking-neural","title":"Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding","date":"2016-04-15","arxiv_id":"1604.04383","repositories_listed":0,"syntology":null},{"url":null,"slug":"scan-attend-and-read-end-to-end-handwritten","title":"Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention","date":"2016-04-12","arxiv_id":"1604.03286","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-compact-recurrent-neural-networks","title":"Learning Compact Recurrent Neural Networks","date":"2016-04-09","arxiv_id":"1604.02594","repositories_listed":0,"syntology":null},{"url":null,"slug":"advances-in-very-deep-convolutional-neural","title":"Advances in Very Deep Convolutional Neural Networks for LVCSR","date":"2016-04-06","arxiv_id":"1604.01792","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiable-pooling-for-unsupervised","title":"Differentiable Pooling for Unsupervised Acoustic Model Adaptation","date":"2016-03-31","arxiv_id":"1603.09630","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-multiscale-features-directly-from","title":"Learning Multiscale Features Directly From Waveforms","date":"2016-03-31","arxiv_id":"1603.09509","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-attention-models-for-sequence","title":"Neural Attention Models for Sequence Classification: Analysis and Application to Key Term Extraction and Dialogue Act Detection","date":"2016-03-31","arxiv_id":"1604.00077","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-interpolation-with-trans-dimensional","title":"Model Interpolation with Trans-dimensional Random Field Language Models for Speech Recognition","date":"2016-03-30","arxiv_id":"1603.09170","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-compression-of-recurrent-neural","title":"On the Compression of Recurrent Neural Networks with an Application to LVCSR acoustic modeling for Embedded Speech Recognition","date":"2016-03-25","arxiv_id":"1603.08042","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-tutorial-on-deep-neural-networks-for","title":"A Tutorial on Deep Neural Networks for Intelligent Systems","date":"2016-03-23","arxiv_id":"1603.07249","repositories_listed":0,"syntology":null},{"url":null,"slug":"acceleration-of-deep-neural-network-training","title":"Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices","date":"2016-03-23","arxiv_id":"1603.07341","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparison-between-deep-neural-nets-and","title":"A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition","date":"2016-03-18","arxiv_id":"1603.05800","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-speech-recognition-on-mobile","title":"Personalized Speech recognition on mobile devices","date":"2016-03-10","arxiv_id":"1603.03185","repositories_listed":0,"syntology":null},{"url":"/paper/segmental-recurrent-neural-networks-for-end","slug":"segmental-recurrent-neural-networks-for-end","title":"Segmental Recurrent Neural Networks for End-to-end Speech Recognition","date":"2016-03-01","arxiv_id":"1603.00223","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-frequency-cepstral-coefficients-for","title":"Adaptive Frequency Cepstral Coefficients for Word Mispronunciation Detection","date":"2016-02-25","arxiv_id":"1602.08132","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-ibm-2016-speaker-recognition-system","title":"The IBM 2016 Speaker Recognition System","date":"2016-02-23","arxiv_id":"1602.07291","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-on-fpgas-past-present-and","title":"Deep Learning on FPGAs: Past, Present, and Future","date":"2016-02-13","arxiv_id":"1602.04283","repositories_listed":0,"syntology":null},{"url":null,"slug":"signer-independent-fingerspelling-recognition","title":"Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation","date":"2016-02-13","arxiv_id":"1602.04278","repositories_listed":0,"syntology":null},{"url":null,"slug":"lipreading-with-long-short-term-memory","title":"Lipreading with Long Short-Term Memory","date":"2016-01-29","arxiv_id":"1601.08188","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligent-conversational-bot-for-massive","title":"Intelligent Conversational Bot for Massive Online Open Courses (MOOCs)","date":"2016-01-26","arxiv_id":"1601.07065","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-recognition-of-element-classes-and","title":"Automatic recognition of element classes and boundaries in the birdsong with variable sequences","date":"2016-01-23","arxiv_id":"1601.06248","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-low-dimensional-structures-to","title":"Exploiting Low-dimensional Structures to Enhance DNN Based Acoustic Modeling in Speech Recognition","date":"2016-01-22","arxiv_id":"1601.05936","repositories_listed":0,"syntology":null},{"url":null,"slug":"manifold-kernels-comparison-in-mkpls-for","title":"Manifold-Kernels Comparison in MKPLS for Visual Speech Recognition","date":"2016-01-22","arxiv_id":"1601.05861","repositories_listed":0,"syntology":null},{"url":null,"slug":"implicit-distortion-and-fertility-models-for","title":"Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model","date":"2016-01-13","arxiv_id":"1601.03317","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-hidden-unit-contributions-for","title":"Learning Hidden Unit Contributions for Unsupervised Acoustic Model Adaptation","date":"2016-01-12","arxiv_id":"1601.02828","repositories_listed":0,"syntology":null},{"url":null,"slug":"environmental-noise-embeddings-for-robust","title":"Environmental Noise Embeddings for Robust Speech Recognition","date":"2016-01-11","arxiv_id":"1601.02553","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-performance-of-a-speech","title":"Evaluating the Performance of a Speech Recognition based System","date":"2016-01-11","arxiv_id":"1601.02543","repositories_listed":0,"syntology":null},{"url":null,"slug":"minimally-supervised-number-normalization","title":"Minimally Supervised Number Normalization","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"feedforward-sequential-memory-networks-a-new","title":"Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency","date":"2015-12-28","arxiv_id":"1512.08301","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-and-computational-guarantees-for","title":"Statistical and Computational Guarantees for the Baum-Welch Algorithm","date":"2015-12-27","arxiv_id":"1512.08269","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-advances-in-convolutional-neural-1","title":"Recent Advances in Convolutional Neural Networks","date":"2015-12-22","arxiv_id":"1512.07108","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-2015-sheffield-system-for-transcription","title":"The 2015 Sheffield System for Transcription of Multi-Genre Broadcast Media","date":"2015-12-21","arxiv_id":"1512.06643","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-pretrained-neural-networks-detect-anatomy","title":"Can Pretrained Neural Networks Detect Anatomy?","date":"2015-12-18","arxiv_id":"1512.05986","repositories_listed":0,"syntology":null},{"url":null,"slug":"small-footprint-deep-neural-networks-with","title":"Small-footprint Deep Neural Networks with Highway Connections for Speech Recognition","date":"2015-12-14","arxiv_id":"1512.04280","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-algorithms-with-applications-to","title":"Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey","date":"2015-12-10","arxiv_id":"1512.03131","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-single-and-multi-session-i","title":"Deep Learning for Single and Multi-Session i-Vector Speaker Recognition","date":"2015-12-08","arxiv_id":"1512.02560","repositories_listed":0,"syntology":null},{"url":null,"slug":"development-of-speech-corpora-for-different","title":"Development of Speech corpora for different Speech Recognition tasks in Malayalam language","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-modulation-spectrum","title":"調變頻譜分解技術於強健語音辨識之研究 (Investigating Modulation Spectrum Factorization Techniques for Robust Speech Recognition) [In Chinese]","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"listening-with-your-eyes-towards-a-practical","title":"Listening With Your Eyes: Towards a Practical Visual Speech Recognition System Using Deep Boltzmann Machines","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-short-survey-on-data-clustering-algorithms","title":"A Short Survey on Data Clustering Algorithms","date":"2015-11-25","arxiv_id":"1511.09123","repositories_listed":0,"syntology":null},{"url":null,"slug":"spoken-language-translation-for-polish","title":"Spoken Language Translation for Polish","date":"2015-11-24","arxiv_id":"1511.07788","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-sequence-training-of-recurrent-neural","title":"Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification","date":"2015-11-21","arxiv_id":"1511.06841","repositories_listed":0,"syntology":null},{"url":null,"slug":"blending-lstms-into-cnns","title":"Blending LSTMs into CNNs","date":"2015-11-19","arxiv_id":"1511.06433","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":"transfer-learning-for-speech-and-language","title":"Transfer Learning for Speech and Language Processing","date":"2015-11-19","arxiv_id":"1511.06066","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancements-in-statistical-spoken-language","title":"Enhancements in statistical spoken language translation by de-normalization of ASR results","date":"2015-11-18","arxiv_id":"1511.09392","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-retrieve-out-of-vocabulary-words","title":"Learning to retrieve out-of-vocabulary words in speech recognition","date":"2015-11-17","arxiv_id":"1511.05389","repositories_listed":0,"syntology":null}],"record_sha256":"31d50e7f9fea5c1d671143793db27881a62c1d92454654ce07d3ea71756e23dd","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}