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 26512700 of 6433 papers

TitleStatusHype
ICASSP 2022 Acoustic Echo Cancellation ChallengeCode2
Integrating Text Inputs For Training and Adapting RNN Transducer ASR Models0
Visual Speech Recognition for Multiple Languages in the WildCode2
A Survey of Multilingual Models for Automatic Speech Recognition0
Language technology practitioners as language managers: arbitrating data bias and predictive bias in ASR0
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech RecognitionCode1
Ask2Mask: Guided Data Selection for Masked Speech Modeling0
Towards Better Meta-Initialization with Task Augmentation for Kindergarten-aged Speech Recognition0
Closing the Gap between Single-User and Multi-User VoiceFilter-Lite0
Differentially Private Speaker Anonymization0
Korean Tokenization for Beam Search Rescoring in Speech Recognition0
Improving CTC-based speech recognition via knowledge transferring from pre-trained language modelsCode0
VADOI:Voice-Activity-Detection Overlapping Inference For End-to-end Long-form Speech Recognition0
FlowSense: Monitoring Airflow in Building Ventilation Systems Using Audio SensingCode0
Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey0
Spanish and English Phoneme Recognition by Training on Simulated Classroom Audio Recordings of Collaborative Learning EnvironmentsCode0
r-G2P: Evaluating and Enhancing Robustness of Grapheme to Phoneme Conversion by Controlled noise introducing and Contextual information incorporation0
The PCG-AIID System for L3DAS22 Challenge: MIMO and MISO convolutional recurrent Network for Multi Channel Speech Enhancement and Speech Recognition0
Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition0
SemEval 2022 Task 12: Symlink- Linking Mathematical Symbols to their Descriptions0
Domain Adaptation of low-resource Target-Domain models using well-trained ASR Conformer Models0
End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system0
'Beach' to 'Bitch': Inadvertent Unsafe Transcription of Kids' Content on YouTube0
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition0
MLP-ASR: Sequence-length agnostic all-MLP architectures for speech recognition0
Curriculum optimization for low-resource speech recognition0
AISHELL-NER: Named Entity Recognition from Chinese SpeechCode1
Conversational Speech Recognition By Learning Conversation-level Characteristics0
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers0
ADIMA: Abuse Detection In Multilingual AudioCode0
Multi-style Training for South African Call Centre Audio0
Learning Contextually Fused Audio-visual Representations for Audio-visual Speech Recognition0
Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference0
Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme0
Multimodal Depression Classification Using Articulatory Coordination Features And Hierarchical Attention Based Text Embeddings0
USTED: Improving ASR with a Unified Speech and Text Encoder-Decoder0
Ultra-low Power Always-on Intelligent and Connected SNN-based System for Multimedia IoT-enabled Applications0
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model DecodingCode0
The Volcspeech system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge0
Enhancing ASR for Stuttered Speech with Limited Data Using Detect and Pass0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications0
Efficient Adapter Transfer of Self-Supervised Speech Models for Automatic Speech RecognitionCode1
T-NGA: Temporal Network Grafting Algorithm for Learning to Process Spiking Audio Sensor Events0
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
The CUHK-TENCENT speaker diarization system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge0
Polyphonic pitch detection with convolutional recurrent neural networks0
Joint Speech Recognition and Audio Captioning0
The RoyalFlush System of Speech Recognition for M2MeT Challenge0
Self-supervised Learning with Random-projection Quantizer for Speech RecognitionCode1
Streaming Multi-Talker ASR with Token-Level Serialized Output TrainingCode1
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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