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 14511500 of 6433 papers

TitleStatusHype
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset0
Analyzing ASR pretraining for low-resource speech-to-text translation0
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition0
A Bayesian Network View on Acoustic Model-Based Techniques for Robust Speech Recognition0
Automatic Speech Recognition Biases in Newcastle English: an Error Analysis0
Analyzing Accuracy Loss in Randomized Smoothing Defenses0
Automatic Speech Recognition (ASR) for the Diagnosis of pronunciation of Speech Sound Disorders in Korean children0
Automatic Speech Recognition: A Shifted Role in Early Speech Intervention?0
Analysis of Visual Features for Continuous Lipreading in Spanish0
Adaptive Audio-Visual Speech Recognition via Matryoshka-Based Multimodal LLMs0
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages0
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition0
Automatic Screening for Children with Speech Disorder using Automatic Speech Recognition: Opportunities and Challenges0
Analysis of Phonetic Transcription for Danish Automatic Speech Recognition0
Adaptive Activation Network For Low Resource Multilingual Speech Recognition0
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition0
Automatic recognition of suprasegmentals in speech0
Automatic recognition of element classes and boundaries in the birdsong with variable sequences0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems0
Automatic recognition of child speech for robotic applications in noisy environments0
Automatic recognition and detection of aphasic natural speech0
Analysis of Manipuri Tones in ManiTo: A Tonal Contrast Database0
Adapting Whisper for Regional Dialects: Enhancing Public Services for Vulnerable Populations in the United Kingdom0
Automatic Quality Estimation for ASR System Combination0
Automatic Pronunciation Scoring And Mispronunciation Detection Using CMUSphinx0
An Analysis of Semantically-Aligned Speech-Text Embeddings0
AUTOMATIC PRONUNCIATION MISTAKE DETECTOR PROJECT REPORT0
Automatic Pronunciation Generation by Utilizing a Semi-supervised Deep Neural Networks0
Analysis of GlobalPhone and Ethiopian Languages Speech Corpora for Multilingual ASR0
Adapting Whisper for Code-Switching through Encoding Refining and Language-Aware Decoding0
A Bayesian Approach to Recurrence in Neural Networks0
SynesLM: A Unified Approach for Audio-visual Speech Recognition and Translation via Language Model and Synthetic Data0
Persian Signature Verification using Fully Convolutional Networks0
Analysis of Deep Clustering as Preprocessing for Automatic Speech Recognition of Sparsely Overlapping Speech0
Automatic pronunciation assessment for language learners with acoustic-phonetic features0
Automatic Long Audio Alignment and Confidence Scoring for Conversational Arabic Speech0
Automatic Learning of Subword Dependent Model Scales0
Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish0
Automatic generation of a 3D sign language avatar on AR glasses given 2D videos of human signers0
Analysis of Dysarthric Speech using Distinctive Feature Recognition0
Automatic evaluation of spoken summaries: the case of language assessment0
Automatic Estimation of Intelligibility Measure for Consonants in Speech0
Analysis of dropout learning regarded as ensemble learning0
Adapting Text-based Dialogue State Tracker for Spoken Dialogues0
A Comparative Study on Speaker-attributed Automatic Speech Recognition in Multi-party Meetings0
Automatic Enhancement of LTAG Treebank0
Automatic dysfluency detection in dysarthric speech using deep belief networks0
Analysis of Dropout in Online Learning0
Automatic Documentation of ICD Codes with Far-Field Speech Recognition0
Analysis and Tuning of a Voice Assistant System for Dysfluent Speech0
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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