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 9511000 of 6433 papers

TitleStatusHype
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition0
Avanc\'ees dans le domaine de la transcription automatique par d\'ecodage guid\'e (Improvements on driven decoding system combination) [in French]0
Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition0
A Variational EM Method for Pole-Zero Modeling of Speech with Mixed Block Sparse and Gaussian Excitation0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning0
A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems0
Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations0
AV-CPL: Continuous Pseudo-Labeling for Audio-Visual Speech Recognition0
AV-data2vec: Self-supervised Learning of Audio-Visual Speech Representations with Contextualized Target Representations0
Avengers, Ensemble! Benefits of ensembling in grapheme-to-phoneme prediction0
AVFormer: Injecting Vision into Frozen Speech Models for Zero-Shot AV-ASR0
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard0
A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers0
Audio-AdapterFusion: A Task-ID-free Approach for Efficient and Non-Destructive Multi-task Speech Recognition0
An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution0
A Voice Controlled E-Commerce Web Application0
A Local Detection Approach for Named Entity Recognition and Mention Detection0
Atypical Prosodic Structure as an Indicator of Reading Level and Text Difficulty0
A Wavelet Transform Based Scheme to Extract Speech Pitch and Formant Frequencies0
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability0
A Web Application for Automated Dialect Analysis0
A Web Service for Pre-segmenting Very Long Transcribed Speech Recordings0
A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks0
Babler - Data Collection from the Web to Support Speech Recognition and Keyword Search0
Atypical Inputs in Educational Applications0
Almost Unsupervised Text to Speech and Automatic Speech Recognition0
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models0
Adaptable End-to-End ASR Models using Replaceable Internal LMs and Residual Softmax0
Back-Translation-Style Data Augmentation for End-to-End ASR0
Balancing Speech Understanding and Generation Using Continual Pre-training for Codec-based Speech LLM0
An Efficient and Effective Online Sentence Segmenter for Simultaneous Interpretation0
Improving OOV Detection and Resolution with External Language Models in Acoustic-to-Word ASR0
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods0
BanglaNum -- A Public Dataset for Bengali Digit Recognition from Speech0
Bangla-Wave: Improving Bangla Automatic Speech Recognition Utilizing N-gram Language Models0
BANSpEmo: A Bangla Emotional Speech Recognition Dataset0
BART based semantic correction for Mandarin automatic speech recognition system0
BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR0
Bilingual Streaming ASR with Grapheme units and Auxiliary Monolingual Loss0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications0
A two-stage transliteration approach to improve performance of a multilingual ASR0
Batched Low-Rank Adaptation of Foundation Models0
Batch-normalized joint training for DNN-based distant speech recognition0
Batch Normalized Recurrent Neural Networks0
Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data0
An Empirical Study of Automatic Chinese Word Segmentation for Spoken Language Understanding and Named Entity Recognition0
Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition0
An Empirical Study of Efficient ASR Rescoring with Transformers0
Bayesian Neural Networks: An Introduction and Survey0
A Tutorial on Deep Neural Networks for Intelligent Systems0
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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