SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 58015850 of 6433 papers

TitleStatusHype
Highway Long Short-Term Memory RNNs for Distant Speech Recognition0
Structured Transforms for Small-Footprint Deep Learning0
Batch Normalized Recurrent Neural Networks0
Deep convolutional acoustic word embeddings using word-pair side informationCode0
類神經網路訓練結合環境群集及專家混合系統於強健性語音辨識(Automatic Speech Recognition using Neural Network based Acoustic Model with the Environment Clustering and Mixture of Experts Algorithms) [In Chinese]0
調變頻譜分解之改良於強健性語音辨識(Several Refinements of Modulation Spectrum Factorization for Robust Speech Recognition) [In Chinese]0
運用Python結合語音辨識及合成技術於自動化音文同步之實作(A Python Implementation of Automatic Speech-text Synchronization Using Speech Recognition and Text-to-Speech Technology)[In Chinese]0
使用詞向量表示與概念資訊於中文大詞彙連續語音辨識之語言模型調適(Exploring Word Embedding and Concept Information for Language Model Adaptation in Mandarin Large Vocabulary Continuous Speech Recognition) [In Chinese]0
表示法學習技術於節錄式語音文件摘要之研究(A Study on Representation Learning Techniques for Extractive Spoken Document Summarization) [In Chinese]0
High-order Graph-based Neural Dependency ParsingCode0
An Improved Hierarchical Word Sequence Language Model Using Directional Information0
Automatic Classification of Spoken Languages using Diverse Acoustic Features0
Real-Time Statistical Speech Translation0
Very Deep Multilingual Convolutional Neural Networks for LVCSR0
Noise-Robust ASR for the third 'CHiME' Challenge Exploiting Time-Frequency Masking based Multi-Channel Speech Enhancement and Recurrent Neural Network0
Mapping Generative Models onto a Network of Digital Spiking Neurons0
Automatic Dialect Detection in Arabic Broadcast SpeechCode0
Noise Robust IOA/CAS Speech Separation and Recognition System For The Third 'CHIME' Challenge0
Evaluating the visualization of what a Deep Neural Network has learnedCode1
The USFD Spoken Language Translation System for IWSLT 20140
Unsupervised Domain Discovery using Latent Dirichlet Allocation for Acoustic Modelling in Speech Recognition0
Data-selective Transfer Learning for Multi-Domain Speech Recognition0
Enhancement and Recognition of Reverberant and Noisy Speech by Extending Its Coherence0
Error Analysis and Improving Speech Recognition for Latvian Language0
Cross-lingual Synonymy Overlap0
An LDA-based Topic Selection Approach to Language Model Adaptation for Handwritten Text Recognition0
Readability Assessment of Translated Texts0
Statistical Machine Translation Improvement based on Phrase Selection0
Speech and language technologies for the automatic monitoring and training of cognitive functions0
Recognition of Distress Calls in Distant Speech Setting: a Preliminary Experiment in a Smart Home0
Remote Speech Technology for Speech Professionals - the CloudCAST initiative0
Contour-based Hand Pose Recognition for Sign Language Recognition0
Model adaptation and adaptive training for the recognition of dysarthric speech0
Predicting disordered speech comprehensibility from Goodness of Pronunciation scores0
Human-Machine Dialogue as a Stochastic Game0
Keynote: Graph-based Approaches for Spoken Language Understanding0
Evaluation of Crowdsourced User Input Data for Spoken Dialog Systems0
Analysis of Dysarthric Speech using Distinctive Feature Recognition0
Data Selection With Fewer Words0
Learning Domain-Independent Dialogue Policies via Ontology Parameterisation0
LeBLEU: N-gram-based Translation Evaluation Score for Morphologically Complex Languages0
``So, which one is it?'' The effect of alternative incremental architectures in a high-performance game-playing agent0
Recurrent Polynomial Network for Dialogue State Tracking with Mismatched Semantic Parsers0
Evaluating Spoken Dialogue Processing for Time-Offset Interaction0
User Adaptive Restoration for Incorrectly-Segmented Utterances in Spoken Dialogue Systems0
Determining an Optimal Set of Flesh Points on Tongue, Lips, and Jaw for Continuous Silent Speech Recognition0
Qualitative investigation of the display of speech recognition results for communication with deaf people0
Automated Speech Recognition Technology for Dialogue Interaction with Non-Native Interlocutors0
Dialogue Management based on Multi-domain Corpus0
SHEF-NN: Translation Quality Estimation with Neural Networks0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified