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 16011650 of 6433 papers

TitleStatusHype
Multi-Sentence Grounding for Long-term Instructional Video0
Stable Distillation: Regularizing Continued Pre-training for Low-Resource Automatic Speech RecognitionCode0
Lattice Rescoring Based on Large Ensemble of Complementary Neural Language Models0
Collaborative Learning with Artificial Intelligence Speakers (CLAIS): Pre-Service Elementary Science Teachers' Responses to the Prototype0
Automated speech audiometry: Can it work using open-source pre-trained Kaldi-NL automatic speech recognition?0
SpokesBiz -- an Open Corpus of Conversational Polish0
Efficiency-oriented approaches for self-supervised speech representation learning0
Speaker Mask Transformer for Multi-talker Overlapped Speech Recognition0
Generative linguistic representation for spoken language identification0
Improved Long-Form Speech Recognition by Jointly Modeling the Primary and Non-primary Speakers0
Seq2seq for Automatic Paraphasia Detection in Aphasic SpeechCode0
Conformer-Based Speech Recognition On Extreme Edge-Computing Devices0
OAVA: the open audio-visual archives aggregator0
Generative Context-aware Fine-tuning of Self-supervised Speech Models0
Adaptive Computation Modules: Granular Conditional Computation For Efficient InferenceCode0
Phoneme-aware Encoding for Prefix-tree-based Contextual ASR0
LiteVSR: Efficient Visual Speech Recognition by Learning from Speech Representations of Unlabeled Data0
Leveraging Language ID to Calculate Intermediate CTC Loss for Enhanced Code-Switching Speech Recognition0
IR-UWB Radar-Based Contactless Silent Speech Recognition of Vowels, Consonants, Words, and Phrases0
Towards Automatic Data Augmentation for Disordered Speech Recognition0
Audio-visual fine-tuning of audio-only ASR models0
Attention-Guided Adaptation for Code-Switching Speech Recognition0
FastInject: Injecting Unpaired Text Data into CTC-based ASR training0
On Robustness to Missing Video for Audiovisual Speech Recognition0
USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models0
Efficient Representation of the Activation Space in Deep Neural Networks0
PhasePerturbation: Speech Data Augmentation via Phase Perturbation for Automatic Speech Recognition0
Revisiting the Entropy Semiring for Neural Speech Recognition0
The GUA-Speech System Description for CNVSRC Challenge 20230
Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identification0
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings0
ROSE: A Recognition-Oriented Speech Enhancement Framework in Air Traffic Control Using Multi-Objective LearningCode0
Deep Photonic Reservoir Computer for Speech Recognition0
Revisiting the Role of Label Smoothing in Enhanced Text Sentiment Classification0
Batched Low-Rank Adaptation of Foundation Models0
Keyword spotting -- Detecting commands in speech using deep learning0
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing0
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning0
Optimizing Two-Pass Cross-Lingual Transfer Learning: Phoneme Recognition and Phoneme to Grapheme Translation0
Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition0
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features0
Bigger is not Always Better: The Effect of Context Size on Speech Pre-TrainingCode0
End-to-End Speech-to-Text Translation: A Survey0
Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model0
Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach0
Speech Understanding on Tiny Devices with A Learning CacheCode0
Adapting OpenAI's Whisper for Speech Recognition on Code-Switch Mandarin-English SEAME and ASRU2019 Datasets0
End-to-end Joint Punctuated and Normalized ASR with a Limited Amount of Punctuated Training Data0
Phonetic-aware speaker embedding for far-field speaker verification0
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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