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 13511400 of 6433 papers

TitleStatusHype
Towards Word-Level End-to-End Neural Speaker Diarization with Auxiliary Network0
Augmenting conformers with structured state-space sequence models for online speech recognition0
Unimodal Aggregation for CTC-based Speech RecognitionCode1
Visual Speech Recognition for Languages with Limited Labeled Data using Automatic Labels from WhisperCode1
DiaCorrect: Error Correction Back-end For Speaker DiarizationCode1
Chunked Attention-based Encoder-Decoder Model for Streaming Speech Recognition0
Combining TF-GridNet and Mixture Encoder for Continuous Speech Separation for Meeting Transcription0
Towards Universal Speech Discrete Tokens: A Case Study for ASR and TTS0
Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks0
PromptASR for contextualized ASR with controllable styleCode2
Echotune: A Modular Extractor Leveraging the Variable-Length Nature of Speech in ASR Tasks0
Incorporating Class-based Language Model for Named Entity Recognition in Factorized Neural Transducer0
CPPF: A contextual and post-processing-free model for automatic speech recognition0
DiariST: Streaming Speech Translation with Speaker DiarizationCode1
CoLLD: Contrastive Layer-to-layer Distillation for Compressing Multilingual Pre-trained Speech Encoders0
Folding Attention: Memory and Power Optimization for On-Device Transformer-based Streaming Speech Recognition0
Hybrid Attention-based Encoder-decoder Model for Efficient Language Model Adaptation0
EnCodecMAE: Leveraging neural codecs for universal audio representation learningCode1
FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech CodecCode2
Enhancing Child Vocalization Classification with Phonetically-Tuned Embeddings for Assisting Autism Diagnosis0
Open-vocabulary Keyword-spotting with Adaptive Instance Normalization0
Can Whisper perform speech-based in-context learning?0
Co-learning synaptic delays, weights and adaptation in spiking neural networks0
Improving Robustness of Neural Inverse Text Normalization via Data-Augmentation, Semi-Supervised Learning, and Post-Aligning Method0
Kid-Whisper: Towards Bridging the Performance Gap in Automatic Speech Recognition for Children VS. Adults0
Hybrid ASR for Resource-Constrained Robots: HMM - Deep Learning FusionCode0
Minuteman: Machine and Human Joining Forces in Meeting Summarization0
Leveraging Large Language Models for Exploiting ASR Uncertainty0
End-to-End Speech Recognition and Disfluency Removal with Acoustic Language Model PretrainingCode0
Active Learning for Classifying 2D Grid-Based Level CompletabilityCode0
Perceptual and Task-Oriented Assessment of a Semantic Metric for ASR EvaluationCode0
Multiple Representation Transfer from Large Language Models to End-to-End ASR Systems0
LanSER: Language-Model Supported Speech Emotion Recognition0
RoDia: A New Dataset for Romanian Dialect Identification from SpeechCode0
Self-Supervised Masked Digital Elevation Models Encoding for Low-Resource Downstream Tasks0
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models0
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning0
Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation0
SememeASR: Boosting Performance of End-to-End Speech Recognition against Domain and Long-Tailed Data Shift with Sememe Semantic Knowledge0
Mapping AI Arguments in Journalism Studies0
BLSP: Bootstrapping Language-Speech Pre-training via Behavior Alignment of Continuation WritingCode1
Contextual Biasing of Named-Entities with Large Language Models0
Mi-Go: Test Framework which uses YouTube as Data Source for Evaluating Speech Recognition Models like OpenAI's Whisper0
Learning Speech Representation From Contrastive Token-Acoustic Pretraining0
Knowledge Distillation from Non-streaming to Streaming ASR Encoder using Auxiliary Non-streaming Layer0
ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers0
Speech Wikimedia: A 77 Language Multilingual Speech DatasetCode0
Adapting Text-based Dialogue State Tracker for Spoken Dialogues0
Unsupervised Active Learning: Optimizing Labeling Cost-Effectiveness for Automatic Speech Recognition0
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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