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 32513300 of 6433 papers

TitleStatusHype
Private Language Model Adaptation for Speech Recognition0
Neural Dependency Coding inspired Multimodal Fusion0
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition0
Challenges and Opportunities of Speech Recognition for Bengali Language0
Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts0
Optimized Power Normalized Cepstral Coefficients towards Robust Deep Speaker Verification0
Simple and Effective Zero-shot Cross-lingual Phoneme RecognitionCode0
Scenario Aware Speech Recognition: Advancements for Apollo Fearless Steps & CHiME-4 Corpora0
A Lightweight dynamic filter for keyword spotting0
Animal inspired Application of a Variant of Mel Spectrogram for Seismic Data Processing0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation0
On the Difficulty of Segmenting Words with Attention0
Robustness Analysis of Deep Learning Frameworks on Mobile PlatformsCode0
iRNN: Integer-only Recurrent Neural Network0
MeetDot: Videoconferencing with Live Translation Captions0
Audio-Visual Speech Recognition is Worth 32328 Voxels0
Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition0
Model-Based Approach for Measuring the Fairness in ASR0
Multimodal Audio-textual Architecture for Robust Spoken Language Understanding0
Dual-Encoder Architecture with Encoder Selection for Joint Close-Talk and Far-Talk Speech Recognition0
PDAugment: Data Augmentation by Pitch and Duration Adjustments for Automatic Lyrics Transcription0
Utterance-level neural confidence measure for end-to-end children speech recognition0
Improving Streaming Transformer Based ASR Under a Framework of Self-supervised Learning0
Improving Accent Identification and Accented Speech Recognition Under a Framework of Self-supervised Learning0
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech0
LRWR: Large-Scale Benchmark for Lip Reading in Russian language0
Non-autoregressive Transformer with Unified Bidirectional Decoder for Automatic Speech Recognition0
Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection0
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search DegradationCode0
Unsupervised Domain Adaptation Schemes for Building ASR in Low-resource Languages0
A Decidability-Based Loss Function0
Large-vocabulary Audio-visual Speech Recognition in Noisy Environments0
Remember the context! ASR slot error correction through memorization0
Self-Attention Channel Combinator Frontend for End-to-End Multichannel Far-field Speech Recognition0
DeepEMO: Deep Learning for Speech Emotion RecognitionCode0
Complementing Handcrafted Features with Raw Waveform Using a Light-weight Auxiliary ModelCode0
A brief history of AI: how to prevent another winter (a critical review)0
Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks0
Coarse-To-Fine And Cross-Lingual ASR Transfer0
Robustness of end-to-end Automatic Speech Recognition Models – A Case Study using Mozilla DeepSpeech0
Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition0
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding0
Multi-Channel Transformer Transducer for Speech Recognition0
Europarl-ASR: A Large Corpus of Parliamentary Debates for Streaming ASR Benchmarking and Speech Data Filtering/Verbatimization0
A Multimodal Framework for Video Ads Understanding0
Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech0
Goal-driven text descriptions for images0
Injecting Text in Self-Supervised Speech Pretraining0
Improving callsign recognition with air-surveillance data in air-traffic communication0
Grammar Based Speaker Role Identification for Air Traffic Control Speech Recognition0
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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