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 59015950 of 6433 papers

TitleStatusHype
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech RecognitionCode0
AfriHuBERT: A self-supervised speech representation model for African languagesCode0
Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative TrainingCode0
Deep Learning using Linear Support Vector MachinesCode0
Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility PredictionCode0
Deep Learning Models in Speech Recognition: Measuring GPU Energy Consumption, Impact of Noise and Model Quantization for Edge DeploymentCode0
PIER: A Novel Metric for Evaluating What Matters in Code-SwitchingCode0
Effect of Attention and Self-Supervised Speech Embeddings on Non-Semantic Speech TasksCode0
Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural NetworksCode0
Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with SubwordsCode0
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
Independent and automatic evaluation of acoustic-to-articulatory inversion modelsCode0
Deep Learning for Audio Signal ProcessingCode0
Evaluation Phonemic Transcription of Low-Resource Tonal Languages for Language DocumentationCode0
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification TasksCode0
An Online Multilingual Hate speech Recognition SystemCode0
Conformer-based Target-Speaker Automatic Speech Recognition for Single-Channel AudioCode0
Language Technology Programme for Icelandic 2019-2023Code0
Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech RecognitionCode0
Blank Collapse: Compressing CTC emission for the faster decodingCode0
The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTSCode0
A segmental framework for fully-unsupervised large-vocabulary speech recognitionCode0
Swiss Parliaments Corpus, an Automatically Aligned Swiss German Speech to Standard German Text CorpusCode0
Political corpus creation through automatic speech recognition on EU debatesCode0
EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based DecodingCode0
Incremental Training of a Recurrent Neural Network Exploiting a Multi-Scale Dynamic MemoryCode0
Improving Voice Separation by Incorporating End-to-end Speech RecognitionCode0
Improving Unsupervised Sparsespeech Acoustic Models with Categorical ReparameterizationCode0
Improving the Inclusivity of Dutch Speech Recognition by Fine-tuning Whisper on the JASMIN-CGN CorpusCode0
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic DataCode0
Improving speech recognition by revising gated recurrent unitsCode0
A Unified Speaker Adaptation Approach for ASRCode0
ASDF: A Differential Testing Framework for Automatic Speech Recognition SystemsCode0
Deep Learning and Its Applications to Machine Health Monitoring: A SurveyCode0
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation EvaluationCode0
A Framework for Adapting Human-Robot Interaction to Diverse User GroupsCode0
Syllable-Based Sequence-to-Sequence Speech Recognition with the Transformer in Mandarin ChineseCode0
Multimodal Grounding for Sequence-to-Sequence Speech RecognitionCode0
Position Prediction as an Effective Pretraining StrategyCode0
Syllable Subword Tokens for Open Vocabulary Speech Recognition in MalayalamCode0
Large-Scale End-to-End Multilingual Speech Recognition and Language Identification with Multi-Task LearningCode0
Confidence Score Based Speaker Adaptation of Conformer Speech Recognition SystemsCode0
Are Neural Open-Domain Dialog Systems Robust to Speech Recognition Errors in the Dialog History? An Empirical StudyCode0
Scalable Factorized Hierarchical Variational Autoencoder TrainingCode0
Synchronous Speech Recognition and Speech-to-Text Translation with Interactive DecodingCode0
AequeVox: Automated Fairness Testing of Speech Recognition SystemsCode0
Deep Learning: A Critical AppraisalCode0
Speech-Based Visual Question AnsweringCode0
Improving Slot Filling in Spoken Language Understanding with Joint Pointer and AttentionCode0
Multimodal Speech Recognition for Language-Guided Embodied AgentsCode0
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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