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 951–1000 of 6433 papers

TitleStatusHype
Exploring neural oscillations during speech perception via surrogate gradient spiking neural networksCode0
RadioTalk: a large-scale corpus of talk radio transcriptsCode0
Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event LocalizationCode0
Rank-1 Constrained Multichannel Wiener Filter for Speech Recognition in Noisy EnvironmentsCode0
Exploiting Adapters for Cross-lingual Low-resource Speech RecognitionCode0
Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired ListenersCode0
Exploring spectro-temporal features in end-to-end convolutional neural networksCode0
A Gentle Tutorial of Recurrent Neural Network with Error BackpropagationCode0
A Small and Fast BERT for Chinese Medical Punctuation RestorationCode0
RED-ACE: Robust Error Detection for ASR using Confidence EmbeddingsCode0
An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer LearningCode0
Explainability of Speech Recognition Transformers via Gradient-based Attention VisualizationCode0
ASL Trigger Recognition in Mixed Activity/Signing Sequences for RF Sensor-Based User InterfacesCode0
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural NetworksCode0
Explaining Spectrograms in Machine Learning: A Study on Neural Networks for Speech ClassificationCode0
Leveraging Cross-Lingual Transfer Learning in Spoken Named Entity Recognition SystemsCode0
Evaluation of End-to-End Continuous Spanish Lipreading in Different Data ConditionsCode0
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification TasksCode0
Re-Translation Strategies For Long Form, Simultaneous, Spoken Language TranslationCode0
A Simple Way to Initialize Recurrent Networks of Rectified Linear UnitsCode0
Evaluating Variants of wav2vec 2.0 on Affective Vocal Burst TasksCode0
Revisiting Word Embedding for Contrasting MeaningCode0
Evaluation Phonemic Transcription of Low-Resource Tonal Languages for Language DocumentationCode0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
A Generalized Language Model as the Combination of Skipped n-grams and Modified Kneser Ney SmoothingCode0
Evaluating Gammatone Frequency Cepstral Coefficients with Neural Networks for Emotion Recognition from SpeechCode0
Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition ErrorsCode0
Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe DatasetCode0
Exploring TTS without T Using Biologically/Psychologically Motivated Neural Network Modules (ZeroSpeech 2020)Code0
FLEURS: Few-shot Learning Evaluation of Universal Representations of SpeechCode0
Bandwidth Embeddings for Mixed-bandwidth Speech RecognitionCode0
BanglaDialecto: An End-to-End AI-Powered Regional Speech StandardizationCode0
Enriching Rare Word Representations in Neural Language Models by Embedding Matrix AugmentationCode0
Error-preserving Automatic Speech Recognition of Young English Learners' LanguageCode0
Enhancing Quantised End-to-End ASR Models via PersonalisationCode0
Enhanced ASR Robustness to Packet Loss with a Front-End Adaptation NetworkCode0
End-to-end Spoken Language Understanding with Tree-constrained Pointer GeneratorCode0
A segmental framework for fully-unsupervised large-vocabulary speech recognitionCode0
End-to-End Speech Recognition With Joint Dereverberation Of Sub-Band Autoregressive EnvelopesCode0
ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech ToolkitCode0
ASDF: A Differential Testing Framework for Automatic Speech Recognition SystemsCode0
End-to-End Speech Recognition and Disfluency Removal with Acoustic Language Model PretrainingCode0
End-to-End Speech Recognition From the Raw WaveformCode0
End-to-End Learning of Speech 2D Feature-Trajectory for Prosthetic HandsCode0
Leveraging Self-Supervised Models for Automatic Whispered Speech RecognitionCode0
Bayesian Learning for Deep Neural Network AdaptationCode0
End-to-end Audiovisual Speech RecognitionCode0
Bayesian Neural Network Language Modeling for Speech RecognitionCode0
End-to-End Open Vocabulary Keyword Search With Multilingual Neural RepresentationsCode0
End-To-End Speech Recognition Using A High Rank LSTM-CTC Based ModelCode0
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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