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 54015450 of 6433 papers

TitleStatusHype
Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize0
AdVerb: Visually Guided Audio Dereverberation0
Adversarial Attacks and Defense on Texts: A Survey0
Adversarial Attacks and Defenses for Speech Recognition Systems0
Adversarial Attacks on ASR Systems: An Overview0
Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey0
Adversarial Black-Box Attacks on Automatic Speech Recognition Systems using Multi-Objective Evolutionary Optimization0
Adversarial Data Augmentation for Disordered Speech Recognition0
Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition0
Adversarial Feature Learning and Unsupervised Clustering based Speech Synthesis for Found Data with Acoustic and Textual Noise0
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition0
Adversarial Machine Learning in Network Intrusion Detection Systems0
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition0
Adversarial Speaker Adaptation0
Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion0
Adversarial Speech Generation and Natural Speech Recovery for Speech Content Protection0
Adversarial synthesis based data-augmentation for code-switched spoken language identification0
Adversarial Training for Multilingual Acoustic Modeling0
Adversarial Training of End-to-end Speech Recognition Using a Criticizing Language Model0
Adversary Resistant Deep Neural Networks with an Application to Malware Detection0
Advocating Character Error Rate for Multilingual ASR Evaluation0
A Dynamic Programming Algorithm for Computing N-gram Posteriors from Lattices0
A Fast-Converged Acoustic Modeling for Korean Speech Recognition: A Preliminary Study on Time Delay Neural Network0
Affect Recognition in Conversations Using Large Language Models0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding0
A Framework for Synthetic Audio Conversations Generation using Large Language Models0
AfriNames: Most ASR models "butcher" African Names0
AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR0
Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond0
AGADIR: Towards Array-Geometry Agnostic Directional Speech Recognition0
A GEN AI Framework for Medical Note Generation0
A Generalized Framework for Hierarchical Word Sequence Language Model0
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks0
A Generative Model of a Pronunciation Lexicon for Hindi0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking0
Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning0
A GrAF-compliant Indonesian Speech Recognition Web Service on the Language Grid for Transcription Crowdsourcing0
A Hardware-Friendly Algorithm for Scalable Training and Deployment of Dimensionality Reduction Models on FPGA0
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding0
AHD ConvNet for Speech Emotion Classification0
A hierarchical approach with feature selection for emotion recognition from speech0
A Hierarchical Neural Model for Learning Sequences of Dialogue Acts0
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews0
A higher order Minkowski loss for improved prediction ability of acoustic model in ASR0
A Highly Adaptive Acoustic Model for Accurate Multi-Dialect Speech Recognition0
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition0
A Human Digital Twin Architecture for Knowledge-based Interactions and Context-Aware Conversations0
A Hybrid Machine Learning Framework for Optimizing Crop Selection via Agronomic and Economic Forecasting0
AI and Accessibility: A Discussion of Ethical Considerations0
A.I. based Embedded Speech to Text Using Deepspeech0
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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