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 28012850 of 6433 papers

TitleStatusHype
Phone Based Keyword Spotting for Transcribing Very Low Resource Languages0
Predicting lexical skills from oral reading with acoustic measures0
Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition SystemsCode0
Speech-T: Transducer for Text to Speech and Beyond0
Mixed Precision of Quantization of Transformer Language Models for Speech Recognition0
Mixed Precision Low-bit Quantization of Neural Network Language Models for Speech Recognition0
Joint Modeling of Code-Switched and Monolingual ASR via Conditional Factorization0
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?0
Effect of noise suppression losses on speech distortion and ASR performance0
Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance0
SpeechMoE2: Mixture-of-Experts Model with Improved Routing0
Romanian Speech Recognition Experiments from the ROBIN ProjectCode1
Multi-Channel Multi-Speaker ASR Using 3D Spatial Feature0
Capitalization and Punctuation Restoration: a Survey0
Deep Spoken Keyword Spotting: An Overview0
Switching Independent Vector Analysis and Its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithms0
A comparison of streaming models and data augmentation methods for robust speech recognition0
SLUE: New Benchmark Tasks for Spoken Language Understanding Evaluation on Natural SpeechCode1
Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages0
Lattention: Lattice-attention in ASR rescoring0
A Conformer-based ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement and Speech Separation0
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions0
The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage0
XLS-R: Self-supervised Cross-lingual Speech Representation Learning at ScaleCode1
Subject Enveloped Deep Sample Fuzzy Ensemble Learning Algorithm of Parkinson's Speech Data0
Leveraging Uni-Modal Self-Supervised Learning for Multimodal Audio-visual Speech Recognition0
Progressive Down-Sampling for Acoustic Encoding0
Two Front-Ends, One Model : Fusing Heterogeneous Speech Features for Low Resource ASR with Multilingual Pre-Training0
Self-supervised Semantic-driven Phoneme Discovery for Zero-resource Speech RecognitionCode0
Speech-to-SQL Parsing: Error Correction with Multi-modal Representations0
Heterogeneous Language Model Optimization in Automatic Speech Recognition0
Improving Multimodal Speech Recognition by Data Augmentation and Speech Representations0
Unified Speech-Text Pre-training for Speech Translation and Recognition0
Who Are We Talking About? Handling Person Names in Speech Translation0
A Novel End-to-End CAPT System for L2 Children Learners0
Modeling speech recognition and synthesis simultaneously: Encoding and decoding lexical and sublexical semantic information into speech with no access to speech data0
On Spoken Language Understanding Systems for Low Resourced Languages0
Speech Synthesis for Low Resource Languages using Transliteration Enabled Transfer Learning0
Attention-based Multi-hypothesis Fusion for Speech SummarizationCode0
Unsupervised Speech Enhancement with speech recognition embedding and disentanglement losses0
Integrated Semantic and Phonetic Post-correction for Chinese Speech RecognitionCode0
Attention based end to end Speech Recognition for Voice Search in Hindi and English0
Joint Unsupervised and Supervised Training for Multilingual ASR0
Analysis of Data Augmentation Methods for Low-Resource Maltese ASR0
Binary classification of spoken words with passive phononic metamaterials0
Prediction of Listener Perception of Argumentative Speech in a Crowdsourced Dataset Using (Psycho-)Linguistic and Fluency Features0
Measuring the Contribution of Multiple Model Representations in Detecting Adversarial InstancesCode0
A Convolutional Neural Network Based Approach to Recognize Bangla Spoken Digits from Speech Signal0
Can neural networks predict dynamics they have never seen?0
Self-Normalized Importance Sampling for Neural Language Modeling0
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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