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 601650 of 6433 papers

TitleStatusHype
Attention-based Audio-Visual Fusion for Robust Automatic Speech RecognitionCode1
Open Source Automatic Speech Recognition for GermanCode1
Zero-shot keyword spotting for visual speech recognition in-the-wildCode1
Word Error Rate Estimation for Speech Recognition: e-WERCode1
Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfacesCode1
RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech RecognitionCode1
Improved training of end-to-end attention models for speech recognitionCode1
Speech Commands: A Dataset for Limited-Vocabulary Speech RecognitionCode1
Attentive Sequence-to-Sequence Learning for Diacritic Restoration of Yorùbá Language TextCode1
Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening ComprehensionCode1
XNMT: The eXtensible Neural Machine Translation ToolkitCode1
Monotonic Chunkwise AttentionCode1
Monotonic Chunkwise AttentionCode1
Minimum Word Error Rate Training for Attention-based Sequence-to-Sequence ModelsCode1
State-of-the-art Speech Recognition With Sequence-to-Sequence ModelsCode1
The DIRHA-English corpus and related tasks for distant-speech recognition in domestic environmentsCode1
AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition BaselineCode1
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural NetworksCode1
Wav2Letter: an End-to-End ConvNet-based Speech Recognition SystemCode1
Single-Channel Multi-Speaker Separation using Deep ClusteringCode1
Communication-Efficient Learning of Deep Networks from Decentralized DataCode1
Deep Speech 2: End-to-End Speech Recognition in English and MandarinCode1
Evaluating the visualization of what a Deep Neural Network has learnedCode1
Listen, Attend and SpellCode1
Attention-Based Models for Speech RecognitionCode1
Deep Speech: Scaling up end-to-end speech recognitionCode1
An exact mapping between the Variational Renormalization Group and Deep LearningCode1
NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speech0
Task-Specific Audio Coding for Machines: Machine-Learned Latent Features Are Codes for That Machine0
WhisperKit: On-device Real-time ASR with Billion-Scale Transformers0
VisualSpeaker: Visually-Guided 3D Avatar Lip Synthesis0
A Hybrid Machine Learning Framework for Optimizing Crop Selection via Agronomic and Economic Forecasting0
First Steps Towards Voice Anonymization for Code-Switching Speech0
Lightweight Target-Speaker-Based Overlap Transcription for Practical Streaming ASR0
AUTOMATIC PRONUNCIATION MISTAKE DETECTOR PROJECT REPORT0
Multimodal Representation Learning and Fusion0
VOICE CONTROL ROBOT USING ARDUINO MANAGEMENT SYSTEM PROJECT.0
AI-Generated Song Detection via Lyrics TranscriptsCode0
End-to-End Spoken Grammatical Error Correction0
Splitformer: An improved early-exit architecture for automatic speech recognition on edge devicesCode0
OpusLM: A Family of Open Unified Speech Language Models0
State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition0
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages0
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization0
Automatic Speech Recognition Biases in Newcastle English: an Error Analysis0
Weight Factorization and Centralization for Continual Learning in Speech Recognition0
Improving Practical Aspects of End-to-End Multi-Talker Speech Recognition for Online and Offline Scenarios0
Thinking in Directivity: Speech Large Language Model for Multi-Talker Directional Speech Recognition0
Unifying Streaming and Non-streaming Zipformer-based ASR0
Bi-directional Context-Enhanced Speech Large Language Models for Multilingual Conversational ASR0
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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