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 21512200 of 6433 papers

TitleStatusHype
Applying LLMs for Rescoring N-best ASR Hypotheses of Casual Conversations: Effects of Domain Adaptation and Context Carry-over0
Applying GPGPU to Recurrent Neural Network Language Model based Fast Network Search in the Real-Time LVCSR0
Cascaded CNN-resBiLSTM-CTC: An End-to-End Acoustic Model For Speech Recognition0
Adversarial Attacks and Defenses for Speech Recognition Systems0
2-bit Conformer quantization for automatic speech recognition0
Casablanca: Data and Models for Multidialectal Arabic Speech Recognition0
CASA-ASR: Context-Aware Speaker-Attributed ASR0
Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection0
CarneliNet: Neural Mixture Model for Automatic Speech Recognition0
Applications of Natural Language Processing in Bilingual Language Teaching: An Indonesian-English Case Study0
Adversarial Attacks and Defense on Texts: A Survey0
A Convolutional Neural Network model based on Neutrosophy for Noisy Speech Recognition0
Enhancing Speech Large Language Models with Prompt-Aware Mixture of Audio Encoders0
Careful Whisper -- leveraging advances in automatic speech recognition for robust and interpretable aphasia subtype classification0
Capturing Multi-Resolution Context by Dilated Self-Attention0
Application of Knowledge Distillation to Multi-task Speech Representation Learning0
Capitalization and Punctuation Restoration: a Survey0
A Convolutional Neural Network Based Approach to Recognize Bangla Spoken Digits from Speech Signal0
Can You Repeat That? Using Word Repetition to Improve Spoken Term Detection0
Can you hear me now? Sensitive comparisons of human and machine perception0
Application-Agnostic Language Modeling for On-Device ASR0
Can You Hear It? Backdoor Attacks via Ultrasonic Triggers0
Can Whisper perform speech-based in-context learning?0
App for Resume-Based Job Matching with Speech Interviews and Grammar Analysis: A Review0
AdVerb: Visually Guided Audio Dereverberation0
Accent Adaptation for the Air Traffic Control Domain0
Enhancing Speech Recognition Decoding via Layer Aggregation0
Enhancing Unsupervised Speech Recognition with Diffusion GANs0
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition0
A Possibilistic Approach for Automatic Word Sense Disambiguation0
Can We Train a Language Model Inside an End-to-End ASR Model? - Investigating Effective Implicit Language Modeling0
A Pilot Study on Arabic Multi-Genre Corpus Diacritization0
A Convexity-based Generalization of Viterbi for Non-Deterministic Weighted Automata0
Can Visual Context Improve Automatic Speech Recognition for an Embodied Agent?0
Cantonese Automatic Speech Recognition Using Transfer Learning from Mandarin0
A Pilot Study of Applying Sequence-to-Sequence Voice Conversion to Evaluate the Intelligibility of L2 Speech Using a Native Speaker's Shadowings0
Can spontaneous spoken language disfluencies help describe syntactic dependencies? An empirical study0
A Wav2vec2-Based Experimental Study on Self-Supervised Learning Methods to Improve Child Speech Recognition0
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts0
Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize0
Accelerator-Aware Training for Transducer-Based Speech Recognition0
Can Pretrained Neural Networks Detect Anatomy?0
Can neural networks predict dynamics they have never seen?0
Can Generative Large Language Models Perform ASR Error Correction?0
Can Discourse Relations be Identified Incrementally?0
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System0
Calm-Whisper: Reduce Whisper Hallucination On Non-Speech By Calming Crazy Heads Down0
A Parameter-efficient Language Extension Framework for Multilingual ASR0
Calibration of Phone Likelihoods in Automatic Speech Recognition0
A Parallel Recurrent Neural Network for Language Modeling with POS Tags0
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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
9Gated ConvNetsWord Error Rate (WER)4.8Unverified
10HMM-TDNN + iVectorsWord 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
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
8DNN MPEPercentage error12.9Unverified
9DNN MMIPercentage error12.9Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage 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
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
7Convolutional Speech RecognitionWord 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