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 52015250 of 6433 papers

TitleStatusHype
Robust Neural Machine Translation with Joint Textual and Phonetic Embedding0
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems0
Robust Prediction of Punctuation and Truecasing for Medical ASR0
Robust Persian Digit Recognition in Noisy Environments Using Hybrid CNN-BiGRU Model0
ROBUST SPEECH COMMAND RECOGNITION USING LABEL-DRIVEN TIME-FREQUENCY MASKING0
Robust speech recognition using consensus function based on multi-layer networks0
Robust Speech Recognition Using Generative Adversarial Networks0
Robust Speech Recognition with Schrödinger Bridge-Based Speech Enhancement0
Robust Spoken Language Understanding with RL-based Value Error Recovery0
Robust Translation of French Live Speech Transcripts0
Role of Intonation in Scoring Spoken English0
Role of non-linear data processing on speech recognition task in the framework of reservoir computing0
Role-specific Language Models for Processing Recorded Neuropsychological Exams0
Romanization Encoding For Multilingual ASR0
Romanized Arabic Transliteration0
融合外部语言知识的流式越南语语音识别(Streaming Vietnamese Speech Recognition Based on Fusing External Vietnamese Language Knowledge)0
RSC: A Romanian Read Speech Corpus for Automatic Speech Recognition0
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition0
Run-and-back stitch search: novel block synchronous decoding for streaming encoder-decoder ASR0
Running Conventional Automatic Speech Recognition on Memristor Hardware: A Simulated Approach0
Run-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising0
RUSAVIC Corpus: Russian Audio-Visual Speech in Cars0
Russian Stress Prediction using Maximum Entropy Ranking0
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus0
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud0
SALAD: Smart AI Language Assistant Daily0
SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generation0
SALM: Speech-augmented Language Model with In-context Learning for Speech Recognition and Translation0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models0
Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems A case study for Modern Greek0
Samrómur Children: An Icelandic Speech Corpus0
Samr\'omur: Crowd-sourcing Data Collection for Icelandic Speech Recognition0
Samrómur: Crowd-sourcing large amounts of data0
SAN: a robust end-to-end ASR model architecture0
SANTLR: Speech Annotation Toolkit for Low Resource Languages0
SapAugment: Learning A Sample Adaptive Policy for Data Augmentation0
SAVAS: Collecting, Annotating and Sharing Audiovisual Language Resources for Automatic Subtitling0
Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme0
SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue0
CIF-T: A Novel CIF-based Transducer Architecture for Automatic Speech Recognition0
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data0
Scalable End-to-End RF Classification: A Case Study on Undersized Dataset Regularization by Convolutional-MST0
Scalable language model adaptation for spoken dialogue systems0
Scalable Multi Corpora Neural Language Models for ASR0
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition0
Scaling and Enhancing LLM-based AVSR: A Sparse Mixture of Projectors Approach0
Scaling A Simple Approach to Zero-Shot Speech Recognition0
Scaling ASR Improves Zero and Few Shot Learning0
Scaling Auditory Cognition via Test-Time Compute in Audio Language Models0
Scaling Laws for Discriminative Speech Recognition Rescoring Models0
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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