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 56015650 of 6433 papers

TitleStatusHype
An Incremental Algorithm for Transition-based CCG Parsing0
An Information-Theoretic View for Deep Learning0
An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition0
An Investigation Into On-device Personalization of End-to-end Automatic Speech Recognition Models0
An Investigation of Enhancing CTC Model for Triggered Attention-based Streaming ASR0
An Investigation of Hybrid architectures for Low Resource Multilingual Speech Recognition system in Indian context0
An investigation of modularity for noise robustness in conformer-based ASR0
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition0
An investigation of phone-based subword units for end-to-end speech recognition0
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech0
An Investigation on Deep Learning with Beta Stabilizer0
An Investigative Study of Multi-Modal Cross-Lingual Retrieval0
An I-vector Based Approach to Compact Multi-Granularity Topic Spaces Representation of Textual Documents0
An LDA-based Topic Selection Approach to Language Model Adaptation for Handwritten Text Recognition0
Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi0
A Noise-Robust Self-supervised Pre-training Model Based Speech Representation Learning for Automatic Speech Recognition0
A Non-autoregressive Model for Joint STT and TTS0
A non-expert Kaldi recipe for Vietnamese Speech Recognition System0
An Online Attention-based Model for Speech Recognition0
An online sequence-to-sequence model for noisy speech recognition0
A Nonparametric Bayesian Approach for Spoken Term detection by Example Query0
An Open Web Platform for Rule-Based Speech-to-Sign Translation0
An Oral History Annotation Tool for INTER-VIEWs0
Another Point of View on Visual Speech Recognition0
An Outlyingness Matrix for Multivariate Functional Data Classification0
A Novel End-to-End CAPT System for L2 Children Learners0
A Novel Method for improving accuracy in neural network by reinstating traditional back propagation technique0
A Novel Self-training Approach for Low-resource Speech Recognition0
A Novel Speech Analysis and Correction Tool for Arabic-Speaking Children0
A Novel Speech-Driven Lip-Sync Model with CNN and LSTM0
A Novel Topology for End-to-end Temporal Classification and Segmentation with Recurrent Neural Network0
An Overview of BPPT's Indonesian Language Resources0
An Overview of Hindi Speech Recognition0
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning0
An Overview on Language Models: Recent Developments and Outlook0
Answer Fast: Accelerating BERT on the Tensor Streaming Processor0
Anti-spoofing Methods for Automatic SpeakerVerification System0
An Ultra-low Power RNN Classifier for Always-On Voice Wake-Up Detection Robust to Real-World Scenarios0
An Unsupervised Approach to User Simulation: Toward Self-Improving Dialog Systems0
An Unsupervised Parameter Estimation Algorithm for a Generative Dependency N-gram Language Model0
An Unsupervised Speaker Clustering Technique based on SOM and I-vectors for Speech Recognition Systems0
序列標記與配對方法用於語音辨識錯誤偵測及修正 (On the Use of Sequence Labeling and Matching Methods for ASR Error Detection and Correction) [In Chinese]0
``Oh, I've Heard That Before'': Modelling Own-Dialect Bias After Perceptual Learning by Weighting Training Data0
A PAC-Bayesian Approach to Minimum Perplexity Language Modeling0
A Panoramic Survey of Natural Language Processing in the Arab World0
A Parallel Recurrent Neural Network for Language Modeling with POS Tags0
A Parameter-efficient Language Extension Framework for Multilingual ASR0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System0
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts0
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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
9Gated ConvNetsWord Error Rate (WER)4.8Unverified
10HMM-TDNN + iVectorsWord 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
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
8DNN MPEPercentage error12.9Unverified
9DNN MMIPercentage error12.9Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage 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
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
7Convolutional Speech RecognitionWord 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