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 801850 of 6433 papers

TitleStatusHype
Automatic Speech Recognition Biases in Newcastle English: an Error Analysis0
Adapter-Based Multi-Agent AVSR Extension for Pre-Trained ASR Models0
Audio-visual Recognition of Overlapped speech for the LRS2 dataset0
A bandit approach to curriculum generation for automatic speech recognition0
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset0
Automatic Speech Recognition for African Low-Resource Languages: Challenges and Future Directions0
Automatic Speech Recognition for Hindi0
Automatic Speech Recognition for Sanskrit with Transfer Learning0
Amharic-English Speech Translation in Tourism Domain0
Audio-visual fine-tuning of audio-only ASR models0
A Comparative Study of LLM-based ASR and Whisper in Low Resource and Code Switching Scenario0
A Methodology for Obtaining Concept Graphs from Word Graphs0
Adaptation Data Selection using Neural Language Models: Experiments in Machine Translation0
Handling Numeric Expressions in Automatic Speech Recognition0
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages0
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network0
Adaptation and Optimization of Automatic Speech Recognition (ASR) for the Maritime Domain in the Field of VHF Communication0
AudioFool: Fast, Universal and synchronization-free Cross-Domain Attack on Speech Recognition0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance0
Ambient Search: A Document Retrieval System for Speech Streams0
A 71.2-μW Speech Recognition Accelerator with Recurrent Spiking Neural Network0
AudioPaLM: A Large Language Model That Can Speak and Listen0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition0
Audio-Visual Decision Fusion for WFST-based and seq2seq Models0
Audio De-identification - a New Entity Recognition Task0
Audio De-identification: A New Entity Recognition Task0
Audio-visual Multi-channel Integration and Recognition of Overlapped Speech0
Audio-visual Multi-channel Recognition of Overlapped Speech0
Audio-visual multi-channel speech separation, dereverberation and recognition0
A Mandarin-English Code-Switching Corpus0
Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model0
A Mixture of Expert Based Deep Neural Network for Improved ASR0
Audio-Visual Speech and Gesture Recognition by Sensors of Mobile Devices0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings0
Audio-Visual Speech Enhancement with Score-Based Generative Models0
Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning0
Audio-Visual Speech Recognition is Worth 32328 Voxels0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks0
Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture0
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition0
Augmented Conversation with Embedded Speech-Driven On-the-Fly Referencing in AR0
A Multi-Biometrics for Twins Identification Based Speech and Ear0
Augmenting Automatic Speech Recognition Models with Disfluency Detection0
Augmenting Bottleneck Features of Deep Neural Network Employing Motor State for Speech Recognition at Humanoid Robots0
Augmenting conformers with structured state-space sequence models for online speech recognition0
Audio-conditioned phonemic and prosodic annotation for building text-to-speech models from unlabeled speech data0
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework0
Augmenting Polish Automatic Speech Recognition System With Synthetic Data0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses0
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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