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 54515500 of 6433 papers

TitleStatusHype
Cross-Lingual Word Embeddings for Low-Resource Language Modeling0
Robust Training under Linguistic AdversityCode0
A Hierarchical Neural Model for Learning Sequences of Dialogue Acts0
Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech0
An experimental analysis of Noise-Contrastive Estimation: the noise distribution matters0
TopologyNet: Topology based deep convolutional neural networks for biomolecular property predictions0
Simplified End-to-End MMI Training and Voting for ASR0
Learning Similarity Functions for Pronunciation Variations0
Efficient Processing of Deep Neural Networks: A Tutorial and Survey0
Batch-normalized joint training for DNN-based distant speech recognition0
Sequence-to-Sequence Models Can Directly Translate Foreign SpeechCode0
A network of deep neural networks for distant speech recognition0
Direct Acoustics-to-Word Models for English Conversational Speech Recognition0
Recognizing Multi-talker Speech with Permutation Invariant Training0
Topic Identification for Speech without ASR0
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines0
Deep LSTM for Large Vocabulary Continuous Speech Recognition0
Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling0
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting0
Multichannel End-to-end Speech Recognition0
Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks0
Comparison of echo state network output layer classification methods on noisy data0
Combining Residual Networks with LSTMs for LipreadingCode0
Deep Reservoir Computing Using Cellular Automata0
English Conversational Telephone Speech Recognition by Humans and Machines0
Exponential Moving Average Model in Parallel Speech Recognition Training0
DECCA Repurposed: Detecting transcription inconsistencies without an orthographic standard0
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling0
Modular Representation of Layered Neural Networks0
CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi0
Residual Convolutional CTC Networks for Automatic Speech Recognition0
Sequence Modeling via SegmentationsCode0
Pronunciation recognition of English phonemes /@/, /æ/, /A:/ and /2/ using Formants and Mel Frequency Cepstral Coefficients0
Multitask Learning with CTC and Segmental CRF for Speech Recognition0
On the Relevance of Auditory-Based Gabor Features for Deep Learning in Automatic Speech Recognition0
A case study on using speech-to-translation alignments for language documentation0
A Morphology-aware Network for Morphological DisambiguationCode0
Towards speech-to-text translation without speech recognition0
Search Intelligence: Deep Learning For Dominant Category Prediction0
Structural Analysis of Hindi Phonetics and A Method for Extraction of Phonetically Rich Sentences from a Very Large Hindi Text Corpus0
A Comprehensive Survey on Bengali Phoneme Recognition0
Learning Word-Like Units from Joint Audio-Visual Analysis0
Deep Network Guided Proof Search0
Regularizing Neural Networks by Penalizing Confident Output DistributionsCode0
First Automatic Fongbe Continuous Speech Recognition System: Development of Acoustic Models and Language ModelsCode0
Lyrics-to-Audio Alignment by Unsupervised Discovery of Repetitive Patterns in Vowel Acoustics0
End-To-End Visual Speech Recognition With LSTMs0
Deep Learning for Computational Chemistry0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading0
End-to-End ASR-free Keyword Search from Speech0
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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