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 901950 of 6433 papers

TitleStatusHype
Automatic recognition of element classes and boundaries in the birdsong with variable sequences0
Automatic recognition of suprasegmentals in speech0
Automatic Screening for Children with Speech Disorder using Automatic Speech Recognition: Opportunities and Challenges0
Audio Attacks and Defenses against AED Systems -- A Practical Study0
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition0
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages0
Automatic Speech Recognition: A Shifted Role in Early Speech Intervention?0
Automatic Speech Recognition (ASR) for the Diagnosis of pronunciation of Speech Sound Disorders in Korean children0
Alternative Pseudo-Labeling for Semi-Supervised Automatic Speech Recognition0
Automatic Speech Recognition Biases in Newcastle English: an Error Analysis0
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset0
Automatic Speech Recognition Errors as a Predictor of L2 Listening Difficulties0
Automatic Speech Recognition for African Low-Resource Languages: Challenges and Future Directions0
Automatic Speech Recognition for Biomedical Data in Bengali Language0
Automatic Speech Recognition for Hindi0
Automatic Speech Recognition for Humanitarian Applications in Somali0
Automatic Speech Recognition for Irish: the ABAIR-ÉIST System0
Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model0
Automatic Speech Recognition for Non-Native English: Accuracy and Disfluency Handling0
Automatic Speech Recognition for Sanskrit with Transfer Learning0
Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement0
Automatic Speech Recognition for the Ika Language0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition0
Automatic Speech Recognition for Uyghur through Multilingual Acoustic Modeling0
Automatic Speech Recognition in German: A Detailed Error Analysis0
Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition0
A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems0
Automatic Speech Recognition of African American English: Lexical and Contextual Effects0
Automatic Speech Recognition of Low-Resource Languages Based on Chukchi0
Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications0
Automatic Speech Recognition on a Firefighter TETRA Broadcast Channel0
Automatic Speech Recognition System-Independent Word Error Rate Estimation0
Automatic Speech Recognition using Advanced Deep Learning Approaches: A survey0
Automatic Speech Recognition And Limited Vocabulary: A Survey0
類神經網路訓練結合環境群集及專家混合系統於強健性語音辨識(Automatic Speech Recognition using Neural Network based Acoustic Model with the Environment Clustering and Mixture of Experts Algorithms) [In Chinese]0
Automatic Speech Recognition Using Template Model for Man-Machine Interface0
Automatic Speech Recognition with BERT and CTC Transformers: A Review0
Automatic Speech Recognition with Very Large Conversational Finnish and Estonian Vocabularies0
Automatic Spoken Language Identification Utilizing Acoustic and Phonetic Speech Information0
Automatic Spoken Language Identification using a Time-Delay Neural Network0
Automatic Syllabification for Manipuri language0
Automatic Text Pronunciation Correlation Generation and Application for Contextual Biasing0
Automatic Transcription Challenges for Inuktitut, a Low-Resource Polysynthetic Language0
Automatic Viseme Vocabulary Construction to Enhance Continuous Lip-reading0
An Application for Building a Polish Telephone Speech Corpus0
Automating speech reception threshold measurements using automatic speech recognition0
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data0
Auto-tuning TensorFlow Threading Model for CPU Backend0
Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition0
Audio-AdapterFusion: A Task-ID-free Approach for Efficient and Non-Destructive Multi-task 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