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 351400 of 6433 papers

TitleStatusHype
End-to-End Speech Recognition and Disfluency RemovalCode1
End-to-End Speech Recognition from Federated Acoustic ModelsCode1
A Hybrid Continuity Loss to Reduce Over-Suppression for Time-domain Target Speaker ExtractionCode1
Enhancing Monotonic Multihead Attention for Streaming ASRCode1
Espresso: A Fast End-to-end Neural Speech Recognition ToolkitCode1
AI Accelerator Survey and TrendsCode1
Evaluating the visualization of what a Deep Neural Network has learnedCode1
Evolutionary Prompt Design for LLM-Based Post-ASR Error CorrectionCode1
Comparative layer-wise analysis of self-supervised speech modelsCode1
CAPE: Encoding Relative Positions with Continuous Augmented Positional EmbeddingsCode1
Can we use Common Voice to train a Multi-Speaker TTS system?Code1
Fast-HuBERT: An Efficient Training Framework for Self-Supervised Speech Representation LearningCode1
CB-Conformer: Contextual biasing Conformer for biased word recognitionCode1
Advancing Test-Time Adaptation in Wild Acoustic Test SettingsCode1
AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition BaselineCode1
A Cross-Modal Approach to Silent Speech with LLM-Enhanced RecognitionCode1
Can Contextual Biasing Remain Effective with Whisper and GPT-2?Code1
A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition BaselineCode1
FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph TransformerCode1
FlowMur: A Stealthy and Practical Audio Backdoor Attack with Limited KnowledgeCode1
Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech RecognitionCode1
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command RecognitionCode1
Generalizing in the Real World with Representation LearningCode1
Generative Pre-Training for Speech with Autoregressive Predictive CodingCode1
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed AudioCode1
Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimationCode1
Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An OverviewCode1
GPU-accelerated Guided Source Separation for Meeting TranscriptionCode1
Gradient Remedy for Multi-Task Learning in End-to-End Noise-Robust Speech RecognitionCode1
Graph Convolutions Enrich the Self-Attention in Transformers!Code1
A context-aware knowledge transferring strategy for CTC-based ASRCode1
HiFi-VC: High Quality ASR-Based Voice ConversionCode1
Byakto Speech: Real-time long speech synthesis with convolutional neural network: Transfer learning from English to BanglaCode1
HypR: A comprehensive study for ASR hypothesis revising with a reference corpusCode1
Bridging the Gaps of Both Modality and Language: Synchronous Bilingual CTC for Speech Translation and Speech RecognitionCode1
Improved acoustic word embeddings for zero-resource languages using multilingual transferCode1
Improved Noisy Student Training for Automatic Speech RecognitionCode1
Improved Open Source Automatic Subtitling for Lecture VideosCode1
Improving Audio-Visual Speech Recognition by Lip-Subword Correlation Based Visual Pre-training and Cross-Modal Fusion EncoderCode1
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge SelectionCode1
Improving Self-supervised Pre-training using Accent-Specific CodebooksCode1
Improving Transformer-based Speech Recognition Using Unsupervised Pre-trainingCode1
Improving Whispered Speech Recognition Performance using Pseudo-whispered based Data AugmentationCode1
AlignVSR: Audio-Visual Cross-Modal Alignment for Visual Speech RecognitionCode1
indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languagesCode1
IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languagesCode1
Interactive Feature Fusion for End-to-End Noise-Robust Speech RecognitionCode1
Investigating the Reordering Capability in CTC-based Non-Autoregressive End-to-End Speech TranslationCode1
A^3T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and EditingCode1
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksCode1
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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
9Gated ConvNetsWord Error Rate (WER)4.8Unverified
10HMM-TDNN + iVectorsWord 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
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
8DNN MPEPercentage error12.9Unverified
9DNN MMIPercentage error12.9Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage 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
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
7Convolutional Speech RecognitionWord 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