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 27012750 of 6433 papers

TitleStatusHype
ASR-Aware End-to-end Neural Diarization0
Error Correction in ASR using Sequence-to-Sequence Models0
RescoreBERT: Discriminative Speech Recognition Rescoring with BERT0
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian0
Language Dependencies in Adversarial Attacks on Speech Recognition Systems0
XLSR53 Wav2Vec2 Portuguese by Orlem SantosCode0
Visualizing Automatic Speech Recognition -- Means for a Better Understanding?0
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy0
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge SelectionCode1
Reducing language context confusion for end-to-end code-switching automatic speech recognition0
Star Temporal Classification: Sequence Classification with Partially Labeled DataCode0
Neural-FST Class Language Model for End-to-End Speech Recognition0
Improving End-to-End Models for Set Prediction in Spoken Language Understanding0
Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognition0
Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition0
Discovering Phonetic Inventories with Crosslingual Automatic Speech RecognitionCode0
On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR0
Internal Language Model Estimation Through Explicit Context Vector Learning for Attention-based Encoder-decoder ASR0
The Norwegian Parliamentary Speech Corpus0
Improving non-autoregressive end-to-end speech recognition with pre-trained acoustic and language models0
Run-and-back stitch search: novel block synchronous decoding for streaming encoder-decoder ASR0
Transformer-Based Video Front-Ends for Audio-Visual Speech Recognition for Single and Multi-Person Video0
Improving the fusion of acoustic and text representations in RNN-T0
Endpoint Detection for Streaming End-to-End Multi-talker ASR0
Investigation of Deep Neural Network Acoustic Modelling Approaches for Low Resource Accented Mandarin Speech Recognition0
Data and knowledge-driven approaches for multilingual training to improve the performance of speech recognition systems of Indian languages0
Variational Auto-Encoder Based Variability Encoding for Dysarthric Speech Recognition0
PickNet: Real-Time Channel Selection for Ad Hoc Microphone Arrays0
Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer0
A Noise-Robust Self-supervised Pre-training Model Based Speech Representation Learning for Automatic Speech Recognition0
Human and Automatic Speech Recognition Performance on German Oral History Interviews0
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR0
DUAL: Textless Spoken Question Answering with Speech Discrete Unit Adaptive Learning0
RED-ACE: Robust Error Detection for ASR using Confidence Embeddings0
Recent Progress in the CUHK Dysarthric Speech Recognition System0
Investigation of Data Augmentation Techniques for Disordered Speech Recognition0
Spectro-Temporal Deep Features for Disordered Speech Assessment and Recognition0
The Effectiveness of Time Stretching for Enhancing Dysarthric Speech for Improved Dysarthric Speech Recognition0
Learning to Enhance or Not: Neural Network-Based Switching of Enhanced and Observed Signals for Overlapping Speech Recognition0
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command RecognitionCode1
A Likelihood Ratio based Domain Adaptation Method for E2E Models0
Cross-Modal ASR Post-Processing System for Error Correction and Utterance Rejection0
Neural Architecture Search For LF-MMI Trained Time Delay Neural NetworksCode0
Two-Pass End-to-End ASR Model Compression0
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset0
Textual Data Augmentation for Arabic-English Code-Switching Speech Recognition0
Improving Mandarin End-to-End Speech Recognition with Word N-gram Language ModelCode1
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster PredictionCode2
Robust Self-Supervised Audio-Visual Speech RecognitionCode2
Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Question0
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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