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 37513800 of 6433 papers

TitleStatusHype
Developing Real-time Streaming Transformer Transducer for Speech Recognition on Large-scale Dataset0
Rethinking Evaluation in ASR: Are Our Models Robust Enough?Code0
Self-training and Pre-training are Complementary for Speech RecognitionCode0
SlimIPL: Language-Model-Free Iterative Pseudo-Labeling0
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks0
LSTM-LM with Long-Term History for First-Pass Decoding in Conversational Speech Recognition0
Towards End-to-End Training of Automatic Speech Recognition for Nigerian PidginCode0
VenoMave: Targeted Poisoning Against Speech RecognitionCode0
FastEmit: Low-latency Streaming ASR with Sequence-level Emission RegularizationCode0
Sentence Boundary Augmentation For Neural Machine Translation Robustness0
Knowledge Distillation for Improved Accuracy in Spoken Question Answering0
Emformer: Efficient Memory Transformer Based Acoustic Model For Low Latency Streaming Speech Recognition0
Cascaded Models With Cyclic Feedback For Direct Speech Translation0
Replacing Human Audio with Synthetic Audio for On-device Unspoken Punctuation Prediction0
Knowledge Transfer for Efficient On-device False Trigger Mitigation0
Pushing the Limits of Semi-Supervised Learning for Automatic Speech RecognitionCode1
Speaker Separation Using Speaker Inventories and Estimated Speech0
Reduce and Reconstruct: ASR for Low-Resource Phonetic Languages0
Ensemble Chinese End-to-End Spoken Language Understanding for Abnormal Event Detection from audio stream0
Towards Data Distillation for End-to-end Spoken Conversational Question Answering0
Studying the Similarity of COVID-19 Sounds based on Correlation Analysis of MFCC0
Non-intrusive speech intelligibility prediction using automatic speech recognition derived measures0
Multimodal Speech Recognition with Unstructured Audio Masking0
Lightweight End-to-End Speech Recognition from Raw Audio Data Using Sinc-Convolutions0
Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An OverviewCode1
Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification0
Towards Resistant Audio Adversarial ExamplesCode1
Dual-mode ASR: Unify and Improve Streaming ASR with Full-context Modeling0
Improving Low Resource Code-switched ASR using Augmented Code-switched TTS0
A Lightweight Speaker Recognition System Using Timbre Properties0
The "Sound of Silence" in EEG -- Cognitive voice activity detection0
fairseq S2T: Fast Speech-to-Text Modeling with fairseqCode0
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers0
Transfer Learning and SpecAugment applied to SSVEP Based BCI Classification0
Non-Attentive Tacotron: Robust and Controllable Neural TTS Synthesis Including Unsupervised Duration ModelingCode1
Population Based Training for Data Augmentation and Regularization in Speech Recognition0
Domain Adversarial Neural Networks for Dysarthric Speech Recognition0
WER we are and WER we think we are0
Transformer Transducer: One Model Unifying Streaming and Non-streaming Speech Recognition0
Representation Learning for Sequence Data with Deep Autoencoding Predictive ComponentsCode1
Swiss Parliaments Corpus, an Automatically Aligned Swiss German Speech to Standard German Text CorpusCode0
The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTSCode0
Fine-Grained Grounding for Multimodal Speech RecognitionCode0
Explaining Deep Neural Networks0
Online Neural Networks for Change-Point DetectionCode1
Differentiable Weighted Finite-State TransducersCode1
基于拼音约束联合学习的汉语语音识别(Chinese Speech Recognition Based on Pinyin Constraint Joint Learning)0
Transformers: State-of-the-Art Natural Language ProcessingCode0
Improving Vietnamese Named Entity Recognition from Speech Using Word Capitalization and Punctuation Recovery ModelsCode1
End-to-End Spoken Language Understanding Without Full Transcripts0
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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