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 48014850 of 6433 papers

TitleStatusHype
Optimizing Multi-Stuttered Speech Classification: Leveraging Whisper's Encoder for Efficient Parameter Reduction in Automated Assessment0
Optimizing Segmentation Strategies for Simultaneous Speech Translation0
Optimizing Speech Recognition For The Edge0
Optimizing Two-Pass Cross-Lingual Transfer Learning: Phoneme Recognition and Phoneme to Grapheme Translation0
OpusLM: A Family of Open Unified Speech Language Models0
Oracle Teacher: Leveraging Target Information for Better Knowledge Distillation of CTC Models0
Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification0
OTF: Optimal Transport based Fusion of Supervised and Self-Supervised Learning Models for Automatic Speech Recognition0
Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach0
Overcoming Data Scarcity in Multi-Dialectal Arabic ASR via Whisper Fine-Tuning0
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts0
Overcoming the bottleneck in traditional assessments of verbal memory: Modeling human ratings and classifying clinical group membership0
Overfitting Mechanism and Avoidance in Deep Neural Networks0
OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models0
OWSM-Biasing: Contextualizing Open Whisper-Style Speech Models for Automatic Speech Recognition with Dynamic Vocabulary0
OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification0
OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer0
MAC: A unified framework boosting low resource automatic speech recognition0
papago: A Machine Translation Service with Word Sense Disambiguation and Currency Conversion0
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition0
Paraformer-v2: An improved non-autoregressive transformer for noise-robust speech recognition0
Paralinguistic Privacy Protection at the Edge0
Parallel Composition of Weighted Finite-State Transducers0
Parallel Corpora in Mboshi (Bantu C25, Congo-Brazzaville)0
Parallel Corpus for Japanese Spoken-to-Written Style Conversion0
Parallel Rescoring with Transformer for Streaming On-Device Speech Recognition0
Parameter-efficient Adaptation of Multilingual Multimodal Models for Low-resource ASR0
Parameter-Efficient Conformers via Sharing Sparsely-Gated Experts for End-to-End Speech Recognition0
Parameter-efficient Dysarthric Speech Recognition Using Adapter Fusion and Householder Transformation0
Parameter-Efficient Transfer Learning under Federated Learning for Automatic Speech Recognition0
Parity Models: A General Framework for Coding-Based Resilience in ML Inference0
ParlamentParla: A Speech Corpus of Catalan Parliamentary Sessions0
ParlaSpeech-HR - a Freely Available ASR Dataset for Croatian Bootstrapped from the ParlaMint Corpus0
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition0
Part-based Lipreading for Audio-Visual Speech Recognition0
Partial Variable Training for Efficient On-Device Federated Learning0
Partitioning Large Scale Deep Belief Networks Using Dropout0
Part-of-Speech Tagger for Bodo Language using Deep Learning approach0
PATCorrect: Non-autoregressive Phoneme-augmented Transformer for ASR Error Correction0
Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling0
PDAugment: Data Augmentation by Pitch and Duration Adjustments for Automatic Lyrics Transcription0
Perceiver-Prompt: Flexible Speaker Adaptation in Whisper for Chinese Disordered Speech Recognition0
Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human Perception0
Perception of Phonological Assimilation by Neural Speech Recognition Models0
Perception Point: Identifying Critical Learning Periods in Speech for Bilingual Networks0
Perceptual-based deep-learning denoiser as a defense against adversarial attacks on ASR systems0
AeGAN: Time-Frequency Speech Denoising via Generative Adversarial Networks0
Perfect match: Improved cross-modal embeddings for audio-visual synchronisation0
Performance Analysis of Speech Encoders for Low-Resource SLU and ASR in Tunisian Dialect0
Global Performance Disparities Between English-Language Accents in Automatic Speech Recognition0
Show:102550
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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