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 26512700 of 6433 papers

TitleStatusHype
Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspective0
On Comparison of Encoders for Attention based End to End Speech Recognition in Standalone and Rescoring Mode0
Improving the Training Recipe for a Robust Conformer-based Hybrid Model0
Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi0
PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis0
Confidence Score Based Conformer Speaker Adaptation for Speech Recognition0
Pruned RNN-T for fast, memory-efficient ASR training0
Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systems0
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data0
Answer Fast: Accelerating BERT on the Tensor Streaming Processor0
Supervision-Guided Codebooks for Masked Prediction in Speech Pre-training0
The Makerere Radio Speech Corpus: A Luganda Radio Corpus for Automatic Speech Recognition0
Boosting Cross-Domain Speech Recognition with Self-SupervisionCode0
Transfer Learning for Robust Low-Resource Children's Speech ASR with Transformers and Source-Filter Warping0
0/1 Deep Neural Networks via Block Coordinate Descent0
Decoupled Federated Learning for ASR with Non-IID Data0
Developing a Speech Recognition System for Recognizing Tonal Speech Signals Using a Convolutional Neural Network0
DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR0
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition0
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition0
The ZevoMOS entry to VoiceMOS Challenge 20220
Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech0
Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition0
Residual Language Model for End-to-end Speech Recognition0
Transformer-based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project0
Toward Zero Oracle Word Error Rate on the Switchboard Benchmark0
Learning-Based Data Storage [Vision] (Technical Report)0
Investigation of Ensemble features of Self-Supervised Pretrained Models for Automatic Speech Recognition0
Training Neural Networks using SAT solvers0
AHD ConvNet for Speech Emotion Classification0
Revisiting End-to-End Speech-to-Text Translation From Scratch0
Context-based out-of-vocabulary word recovery for ASR systems in Indian languages0
Joint Encoder-Decoder Self-Supervised Pre-training for ASR0
Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos0
LegoNN: Building Modular Encoder-Decoder Models0
FedNST: Federated Noisy Student Training for Automatic Speech Recognition0
Lip-Listening: Mixing Senses to Understand Lips using Cross Modality Knowledge Distillation for Word-Based Models0
Pronunciation Dictionary-Free Multilingual Speech Synthesis by Combining Unsupervised and Supervised Phonetic Representations0
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian0
Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages0
Multilingual Transfer Learning for Children Automatic Speech Recognition0
Automatic Speech Recognition for Irish: the ABAIR-ÉIST System0
DiaBiz – an Annotated Corpus of Polish Call Center Dialogs0
Development of Automatic Speech Recognition for the Documentation of Cook Islands Māori0
Development and Evaluation of Speech Recognition for the Welsh Language0
Developing Automatic Speech Recognition for Scottish Gaelic0
Samrómur: Crowd-sourcing large amounts of data0
Handwriting recognition for Scottish Gaelic0
Standard German Subtitling of Swiss German TV content: the PASSAGE Project0
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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