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 25012550 of 6433 papers

TitleStatusHype
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation0
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition0
Disappeared Command: Spoofing Attack On Automatic Speech Recognition Systems with Sound Masking0
Automated speech tools for helping communities process restricted-access corpora for language revival efforts0
Lombard Effect for Bilingual Speakers in Cantonese and English: importance of spectro-temporal features0
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes0
Study of Indian English Pronunciation Variabilities relative to Received Pronunciation0
Self-critical Sequence Training for Automatic Speech Recognition0
HuBERT-EE: Early Exiting HuBERT for Efficient Speech RecognitionCode0
CorrectSpeech: A Fully Automated System for Speech Correction and Accent Reduction0
ASR in German: A Detailed Error Analysis0
Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding0
Large-Scale Streaming End-to-End Speech Translation with Neural TransducersCode1
Unified Speech-Text Pre-training for Speech Translation and Recognition0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data0
Deep Embeddings for Robust User-Based Amateur Vocal Percussion Classification0
Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility PredictionCode0
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition0
Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired ListenersCode0
Adding Connectionist Temporal Summarization into Conformer to Improve Its Decoder Efficiency For Speech Recognition0
Defense against Adversarial Attacks on Hybrid Speech Recognition using Joint Adversarial Fine-tuning with Denoiser0
Hierarchical Softmax for End-to-End Low-resource Multilingual Speech RecognitionCode0
Personal VAD 2.0: Optimizing Personal Voice Activity Detection for On-Device Speech Recognition0
Detecting Dysfluencies in Stuttering Therapy Using wav2vec 2.00
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model0
MAESTRO: Matched Speech Text Representations through Modality Matching0
3M: Multi-loss, Multi-path and Multi-level Neural Networks for speech recognitionCode1
Enabling All In-Edge Deep Learning: A Literature Review0
A Wav2vec2-Based Experimental Study on Self-Supervised Learning Methods to Improve Child Speech Recognition0
Successes and critical failures of neural networks in capturing human-like speech recognition0
Emotional Speech Recognition with Pre-trained Deep Visual ModelsCode0
Simple and Effective Unsupervised Speech Synthesis0
A survey on recently proposed activation functions for Deep Learning0
Enhanced Direct Speech-to-Speech Translation Using Self-supervised Pre-training and Data Augmentation0
A Complementary Joint Training Approach Using Unpaired Speech and Text for Low-Resource Automatic Speech Recognition0
Unsupervised Data Selection via Discrete Speech Representation for ASR0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective0
Audio-visual multi-channel speech separation, dereverberation and recognition0
Combining Spectral and Self-Supervised Features for Low Resource Speech Recognition and Translation0
Towards End-to-end Unsupervised Speech Recognition0
Low-Latency Speech Separation Guided Diarization for Telephone ConversationsCode1
Hear No Evil: Towards Adversarial Robustness of Automatic Speech Recognition via Multi-Task Learning0
Deliberation Model for On-Device Spoken Language Understanding0
An Analysis of Semantically-Aligned Speech-Text Embeddings0
Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition0
A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems0
Self-Supervised Speech Representations Preserve Speech Characteristics while Anonymizing Voices0
Deep Speech Based End-to-End Automated Speech Recognition (ASR) for Indian-English Accents0
Speaker adaptation for Wav2vec2 based dysarthric ASR0
Fast Real-time Personalized Speech Enhancement: End-to-End Enhancement Network (E3Net) and Knowledge Distillation0
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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