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 23512400 of 6433 papers

TitleStatusHype
BS-PLCNet: Band-split Packet Loss Concealment Network with Multi-task Learning Framework and Multi-discriminators0
Exploitation d'une marge de tol\'erance de classification pour am\'eliorer l'apprentissage de mod\`eles acoustiques de classes en reconnaissance de la parole (Exploitation of a classification tolerance margin for improving the estimation of class-based acoustic models for speech recognition) [in French]0
Can spontaneous spoken language disfluencies help describe syntactic dependencies? An empirical study0
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts0
Exploiting Beam Search Confidence for Energy-Efficient Speech Recognition0
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition0
Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition0
Exploiting Cross-Lingual Knowledge in Unsupervised Acoustic Modeling for Low-Resource Languages0
A Novel Speech-Driven Lip-Sync Model with CNN and LSTM0
Exploiting Cross-Lingual Speaker and Phonetic Diversity for Unsupervised Subword Modeling0
Exploiting Low-dimensional Structures to Enhance DNN Based Acoustic Modeling in Speech Recognition0
Exploiting Low-Resource Code-Switching Data to Mandarin-English Speech Recognition Systems0
Exploiting Machine-Transcribed Dialog Corpus to Improve Multiple Dialog States Tracking Methods0
Exploiting multiple hypotheses for Multilingual Spoken Language Understanding0
Environment-aware Reconfigurable Noise Suppression0
Exploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech0
Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition0
Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding0
Exploiting Single-Channel Speech For Multi-channel End-to-end Speech Recognition0
Exploiting Single-Channel Speech for Multi-Channel End-to-End Speech Recognition: A Comparative Study0
Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification0
Exploiting the large-scale German Broadcast Corpus to boost the Fraunhofer IAIS Speech Recognition System0
Exploration of Adapter for Noise Robust Automatic Speech Recognition0
EXPLORATION OF EFFICIENT ON-DEVICE ACOUSTIC MODELING WITH NEURAL NETWORKS0
Environmental Noise Embeddings for Robust Speech Recognition0
Exploration of Language Dependency for Japanese Self-Supervised Speech Representation Models0
Entity resolution for noisy ASR transcripts0
Exploratory Evaluation of Speech Content Masking0
Exploring Architectures, Data and Units For Streaming End-to-End Speech Recognition with RNN-Transducer0
Exploring Attention Map Reuse for Efficient Transformer Neural Networks0
Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech0
使用概念資訊於中文大詞彙連續語音辨識之研究 (Exploring Concept Information for Mandarin Large Vocabulary Continuous Speech Recognition) [In Chinese]0
Exploring Content Features for Automated Speech Scoring0
Exploring CTC Based End-to-End Techniques for Myanmar Speech Recognition0
Exploring data augmentation in bias mitigation against non-native-accented speech0
Exploring Effective Distillation of Self-Supervised Speech Models for Automatic Speech Recognition0
Exploring End-to-End Techniques for Low-Resource Speech Recognition0
Exploring Energy-based Language Models with Different Architectures and Training Methods for Speech Recognition0
Exploring Features For Localized Detection of Speech Recognition Errors0
Exploring Gender Disparities in Automatic Speech Recognition Technology0
Cascaded CNN-resBiLSTM-CTC: An End-to-End Acoustic Model For Speech Recognition0
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training0
Exploring linguistic feature and model combination for speech recognition based automatic AD detection0
Exploring Machine Speech Chain for Domain Adaptation and Few-Shot Speaker Adaptation0
Exploring Methods for the Automatic Detection of Errors in Manual Transcription0
Cascaded Cross-Modal Transformer for Request and Complaint Detection0
Exploring Neural Transducers for End-to-End Speech Recognition0
Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition0
Entity Linking for Spoken Language0
Broadcast News Story Segmentation Using Manifold Learning on Latent Topic Distributions0
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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