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 11511200 of 6433 papers

TitleStatusHype
Keyword spotting -- Detecting commands in speech using deep learning0
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing0
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning0
Graph Convolutions Enrich the Self-Attention in Transformers!Code1
Optimizing Two-Pass Cross-Lingual Transfer Learning: Phoneme Recognition and Phoneme to Grapheme Translation0
Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition0
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features0
Bigger is not Always Better: The Effect of Context Size on Speech Pre-TrainingCode0
End-to-End Speech-to-Text Translation: A Survey0
Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model0
Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach0
Speech Understanding on Tiny Devices with A Learning CacheCode0
Adapting OpenAI's Whisper for Speech Recognition on Code-Switch Mandarin-English SEAME and ASRU2019 Datasets0
End-to-end Joint Punctuated and Normalized ASR with a Limited Amount of Punctuated Training Data0
D4AM: A General Denoising Framework for Downstream Acoustic ModelsCode1
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature ExtractorsCode0
Phonetic-aware speaker embedding for far-field speaker verification0
Multilingual self-supervised speech representations improve the speech recognition of low-resource African languages with codeswitching0
Weak Alignment Supervision from Hybrid Model Improves End-to-end ASR0
Do VSR Models Generalize Beyond LRS3?Code1
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack DetectionCode0
Analysis of Visual Features for Continuous Lipreading in Spanish0
Soft Random Sampling: A Theoretical and Empirical Analysis0
Speaker-Adapted End-to-End Visual Speech Recognition for Continuous Spanish0
LIP-RTVE: An Audiovisual Database for Continuous Spanish in the WildCode0
App for Resume-Based Job Matching with Speech Interviews and Grammar Analysis: A Review0
How does end-to-end speech recognition training impact speech enhancement artifacts?0
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems0
Label-Synchronous Neural Transducer for Adaptable Online E2E Speech Recognition0
ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding0
GhostVec: A New Threat to Speaker Privacy of End-to-End Speech Recognition System0
Investigating the Emergent Audio Classification Ability of ASR Foundation ModelsCode0
Improving Large-scale Deep Biasing with Phoneme Features and Text-only Data in Streaming Transducer0
Multi-channel Conversational Speaker Separation via Neural Diarization0
Enhanced Generative Adversarial Networks for Unseen Word Generation from EEG Signals0
Retrieve and Copy: Scaling ASR Personalization to Large Catalogs0
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language ModelsCode3
Zero-shot audio captioning with audio-language model guidance and audio context keywordsCode1
On the Effectiveness of ASR Representations in Real-world Noisy Speech Emotion Recognition0
ChatGPT in the context of precision agriculture data analyticsCode0
Improving Whispered Speech Recognition Performance using Pseudo-whispered based Data AugmentationCode1
Whisper in Focus: Enhancing Stuttered Speech Classification with Encoder Layer Optimization0
Towards End-to-End Spoken Grammatical Error Correction0
GPU-Accelerated WFST Beam Search Decoder for CTC-based Speech RecognitionCode1
1SPU: 1-step Speech Processing Unit0
A comparative analysis between Conformer-Transducer, Whisper, and wav2vec2 for improving the child speech recognitionCode0
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer LearningCode1
Fine-tuning convergence model in Bengali speech recognition0
Pseudo-Labeling for Domain-Agnostic Bangla Automatic Speech RecognitionCode0
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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