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 21512200 of 6433 papers

TitleStatusHype
A Survey on Methods and Theories of Quantized Neural Networks0
Conventional Orthography for Dialectal Arabic0
A Survey on Evolutionary Neural Architecture Search0
A kernel for time series based on global alignments0
Controlled Ascent: Imbuing Statistical MT with Linguistic Knowledge0
Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection0
A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms0
Contribution \`a l'\'etude de la variabilit\'e de la voix des personnes \^ag\'ees en reconnaissance automatique de la parole (Contribution to the study of elderly people's voice variability in automatic speech recognition) [in French]0
Contrastive Siamese Network for Semi-supervised Speech Recognition0
Towards a Robust Deep Neural Network in Texts: A Survey0
A Joint Spectro-Temporal Relational Thinking Based Acoustic Modeling Framework0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition0
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers0
Contrastive Semi-supervised Learning for ASR0
A Survey of the Recent Architectures of Deep Convolutional Neural Networks0
Learning Video Representations using Contrastive Bidirectional Transformer0
A Joint Model of Orthography and Morphological Segmentation0
Contour-based Hand Pose Recognition for Sign Language Recognition0
Contour-based 3d tongue motion visualization using ultrasound image sequences0
A Survey of Multilingual Models for Automatic Speech Recognition0
Continuous Speech Separation with Recurrent Selective Attention Network0
Continuous Speech Separation with Ad Hoc Microphone Arrays0
A Joint Approach to Compound Splitting and Idiomatic Compound Detection0
A Crowdsourcing Smartphone Application for Swiss German: Putting Language Documentation in the Hands of the Users0
Continuous Speech Recognition using EEG and Video0
A Supervised STDP-based Training Algorithm for Living Neural Networks0
Continuous Soft Pseudo-Labeling in ASR0
Continuous Sign Language Recognition with Adapted Conformer via Unsupervised Pretraining0
A Subband-Based SVM Front-End for Robust ASR0
Continuous Pseudo-Labeling from the Start0
Continuous multilinguality with language vectors0
A Study on Zero-shot Non-intrusive Speech Assessment using Large Language Models0
Continuous Modeling of the Denoising Process for Speech Enhancement Based on Deep Learning0
Continuously Predicting and Processing Barge-in During a Live Spoken Dialogue Task0
A study on the impact of Self-Supervised Learning on automatic dysarthric speech assessment0
AIx Speed: Playback Speed Optimization Using Listening Comprehension of Speech Recognition Models0
A Closer Look at Wav2Vec2 Embeddings for On-Device Single-Channel Speech Enhancement0
4D ASR: Joint modeling of CTC, Attention, Transducer, and Mask-Predict decoders0
Towards interfacing large language models with ASR systems using confidence measures and prompting0
Continuously Learning New Words in Automatic Speech Recognition0
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding0
Continuous Expressive Speaking Styles Synthesis based on CVSM and MR-HMM0
Continued Pretraining for Domain Adaptation of Wav2vec2.0 in Automatic Speech Recognition for Elementary Math Classroom Settings0
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge0
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning0
表示法學習技術於節錄式語音文件摘要之研究(A Study on Representation Learning Techniques for Extractive Spoken Document Summarization) [In Chinese]0
Towards continually learning new languages0
Continual learning using lattice-free MMI for speech recognition0
A study on native American English speech recognition by Indian listeners with varying word familiarity level0
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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