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 19512000 of 6433 papers

TitleStatusHype
CTC-Assisted LLM-Based Contextual ASR0
CTC Alignments Improve Autoregressive Translation0
Attention based on-device streaming speech recognition with large speech corpus0
Dual Causal/Non-Causal Self-Attention for Streaming End-to-End Speech Recognition0
CS-Dialogue: A 104-Hour Dataset of Spontaneous Mandarin-English Code-Switching Dialogues for Speech Recognition0
Attention-based Neural Beamforming Layers for Multi-channel Speech Recognition0
Cross-Utterance Language Models with Acoustic Error Sampling0
Dual Fixed-Size Ordinally Forgetting Encoding (FOFE) for Competitive Neural Language Models0
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition0
Cross-Modal Transformer-Based Neural Correction Models for Automatic Speech Recognition0
Dual-Pipeline with Low-Rank Adaptation for New Language Integration in Multilingual ASR0
Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference0
Align-Refine: Non-Autoregressive Speech Recognition via Iterative Realignment0
Dual Supervised Learning0
Cross-Modal Mutual Learning for Cued Speech Recognition0
Cross-modal Knowledge Transfer Learning as Graph Matching Based on Optimal Transport for ASR0
Cross-Modal ASR Post-Processing System for Error Correction and Utterance Rejection0
DualVoice: Speech Interaction that Discriminates between Normal and Whispered Voice Input0
DuDe: Dual-Decoder Multilingual ASR for Indian Languages using Common Label Set0
Attention based end to end Speech Recognition for Voice Search in Hindi and English0
Alignment Restricted Streaming Recurrent Neural Network Transducer0
DuTongChuan: Context-aware Translation Model for Simultaneous Interpreting0
DYNAC: Dynamic Vocabulary based Non-Autoregressive Contextualization for Speech Recognition0
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition0
Dynamic Alignment Mask CTC: Improved Mask-CTC with Aligned Cross Entropy0
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model0
Dynamic Behaviour of Connectionist Speech Recognition with Strong Latency Constraints0
Dynamic Chunk Convolution for Unified Streaming and Non-Streaming Conformer ASR0
Cross-modal Alignment with Optimal Transport for CTC-based ASR0
Dynamic Data Pruning for Automatic Speech Recognition0
Cross-Lingual Word Embeddings for Low-Resource Language Modeling0
Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency0
Attention-Based End-to-End Speech Recognition on Voice Search0
Cross-Lingual Transfer Learning for Speech Translation0
Dynamic Latency for CTC-Based Streaming Automatic Speech Recognition With Emformer0
Dynamic latency speech recognition with asynchronous revision0
Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition0
Dynamic Masking for Improved Stability in Spoken Language Translation0
Dynamic Sparsity Neural Networks for Automatic Speech Recognition0
Dynamic web service deployment in a cloud environment0
Dyn-ASR: Compact, Multilingual Speech Recognition via Spoken Language and Accent Identification0
DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognition0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition0
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications0
Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem0
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition0
A comparable study of modeling units for end-to-end Mandarin speech recognition0
融合多任務學習類神經網路聲學模型訓練於會議語音辨識之研究(Leveraging Multi-task Learning with Neural Network Based Acoustic Modeling for Improved Meeting Speech Recognition) [In Chinese]0
融合多任務學習類神經網路聲學模型訓練於會議語音辨識之研究 (Leveraging Multi-Task Learning with Neural Network Based Acoustic Modeling for Improved Meeting Speech Recognition) [In Chinese]0
使用長短期記憶類神經網路建構中文語音辨識器之研究 (A study on Mandarin speech recognition using Long Short-Term Memory neural network) [In Chinese]0
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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