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

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Showing 2551–2600 of 6433 papers

TitleStatusHype
A Novel Method for improving accuracy in neural network by reinstating traditional back propagation technique—0
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization—0
First Steps Towards Voice Anonymization for Code-Switching Speech—0
Fixing Errors of the Google Voice Recognizer through Phonetic Distance Metrics—0
Enhancing Unsupervised Speech Recognition with Diffusion GANs—0
Cloud-Based Face and Speech Recognition for Access Control Applications—0
Accelerating recurrent neural network language model based online speech recognition system—0
Flexible Multichannel Speech Enhancement for Noise-Robust Frontend—0
Gated Low-rank Adaptation for personalized Code-Switching Automatic Speech Recognition on the low-spec devices—0
Enhancing the Unified Streaming and Non-streaming Model with Contrastive Learning—0
Enhancing the TED-LIUM Corpus with Selected Data for Language Modeling and More TED Talks—0
Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech—0
Enhancing Synthetic Training Data for Speech Commands: From ASR-Based Filtering to Domain Adaptation in SSL Latent Space—0
Enhancing Speech Recognition Decoding via Layer Aggregation—0
A Novel End-to-End CAPT System for L2 Children Learners—0
Enhancing Speech Large Language Models with Prompt-Aware Mixture of Audio Encoders—0
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody—0
Folding Attention: Memory and Power Optimization for On-Device Transformer-based Streaming Speech Recognition—0
FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator—0
Foreign English Accent Adjustment by Learning Phonetic Patterns—0
Fotheidil: an Automatic Transcription System for the Irish Language—0
Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models—0
Four-in-One: A Joint Approach to Inverse Text Normalization, Punctuation, Capitalization, and Disfluency for Automatic Speech Recognition—0
FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks—0
FPGA Resource-aware Structured Pruning for Real-Time Neural Networks—0
FPI: Failure Point Isolation in Large-scale Conversational Assistants—0
Free Acoustic and Language Models for Large Vocabulary Continuous Speech Recognition in Swedish—0
Free English and Czech telephone speech corpus shared under the CC-BY-SA 3.0 license—0
Free on-line speech recogniser based on Kaldi ASR toolkit producing word posterior lattices—0
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning—0
Frequency-Directional Attention Model for Multilingual Automatic Speech Recognition—0
Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition—0
From `Solved Problems' to New Challenges: A Report on LDC Activities—0
From Audio to Semantics: Approaches to end-to-end spoken language understanding—0
From Audio to Symbolic Encoding—0
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation—0
From dictations to clinical reports using machine translation—0
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition—0
Cocktail-Party Audio-Visual Speech Recognition—0
From Human Language Technology to Human Language Science—0
Enhancing Neural Spoken Language Recognition: An Exploration with Multilingual Datasets—0
From Nodes to Networks: Evolving Recurrent Neural Networks—0
From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings—0
From Senones to Chenones: Tied Context-Dependent Graphemes for Hybrid Speech Recognition—0
Summarizing Speech: A Comprehensive Survey—0
From Statistical Methods to Pre-Trained Models; A Survey on Automatic Speech Recognition for Resource Scarce Urdu Language—0
From Strangers to Partners: Examining Convergence within a Longitudinal Study of Task-Oriented Dialogue—0
An Outlyingness Matrix for Multivariate Functional Data Classification—0
From Voice to Safety: Language AI Powered Pilot-ATC Communication Understanding for Airport Surface Movement Collision Risk Assessment—0
Advances in All-Neural Speech Recognition—0
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All datasetsLibriSpeech test-cleanLibriSpeech test-otherSwitchboard + Hub500TIMITAISHELL-1WSJ eval92Common Voice Germanswb_hub_500 WER fullSWBCHTUDACommon Voice FrenchCommon Voice SpanishMediaSpeech

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6—Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8—Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19—Unverified
4SnipsWord Error Rate (WER)6.4—Unverified
5Li-GRUWord Error Rate (WER)6.2—Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5—Unverified
7CTC + policy learningWord Error Rate (WER)5.42—Unverified
8Deep Speech 2Word Error Rate (WER)5.33—Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8—Unverified
10Gated ConvNetsWord Error Rate (WER)4.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84—Unverified
2SnipsWord Error Rate (WER)16.5—Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28—Unverified
4Deep Speech 2Word Error Rate (WER)13.25—Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5—Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65—Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47—Unverified
8MT4SSLWord Error Rate (WER)9.6—Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79—Unverified
10EspressoWord Error Rate (WER)8.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20—Unverified
2DNN-HMMPercentage error18.5—Unverified
3CD-DNNPercentage error16.1—Unverified
4DNNPercentage error16—Unverified
5DNN + DropoutPercentage error15—Unverified
6DNN BMMIPercentage error12.9—Unverified
7DNN MPEPercentage error12.9—Unverified
8DNN MMIPercentage error12.9—Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9—Unverified
10HMM-DNN +sMBRPercentage error12.6—Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2—Unverified
2LAS multitask with indicators samplingPercentage error20.4—Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1—Unverified
4QCNN-10L-256FMPercentage error19.64—Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7—Unverified
6Bi-RNN + AttentionPercentage error17.6—Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3—Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7—Unverified
9Light Gated Recurrent UnitsPercentage error16.7—Unverified
10GRUPercentage error16.6—Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7—Unverified
2CTC/AttWord Error Rate (WER)6.7—Unverified
3BRA-EWord Error Rate (WER)6.63—Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34—Unverified
5BATWord Error Rate (WER)4.97—Unverified
6ParaformerWord Error Rate (WER)4.95—Unverified
7U2Word Error Rate (WER)4.72—Unverified
8UMAWord Error Rate (WER)4.7—Unverified
9Lightweight TransducerWord Error Rate (WER)4.31—Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9—Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6—Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79—Unverified
4Deep Speech 2Word Error Rate (WER)3.6—Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6—Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5—Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5—Unverified
8EspressoWord Error Rate (WER)3.4—Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2—Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19—Unverified