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 42514300 of 6433 papers

TitleStatusHype
Speech-Mamba: Long-Context Speech Recognition with Selective State Spaces Models0
Speech-MLP: a simple MLP architecture for speech processing0
SpeechMoE2: Mixture-of-Experts Model with Improved Routing0
SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale0
Speech Pattern based Black-box Model Watermarking for Automatic Speech Recognition0
Speech Rate Calculations with Short Utterances: A Study from a Speech-to-Speech, Machine Translation Mediated Map Task0
Speech ReaLLM -- Real-time Streaming Speech Recognition with Multimodal LLMs by Teaching the Flow of Time0
Speech Recognition-based Feature Extraction for Enhanced Automatic Severity Classification in Dysarthric Speech0
Speech Recognition by Simply Fine-tuning BERT0
Speech recognition for air traffic control via feature learning and end-to-end training0
Speech Recognition for Automatically Assessing Afrikaans and isiXhosa Preschool Oral Narratives0
Speech Recognition for Endangered and Extinct Samoyedic languages0
Speech recognition for medical conversations0
Speech Recognition for Tigrinya language Using Deep Neural Network Approach0
Speech Recognition Front End Without Information Loss0
Speech recognition in Alzheimer's disease with personal assistive robots0
Speech Recognition: Keyword Spotting Through Image Recognition0
語音辨識使用統計圖等化方法 (Speech Recognition Leveraging Histogram Equalization Methods) [In Chinese]0
Speech Recognition on TV Series with Video-guided Post-Correction0
Speech Recognition Rescoring with Large Speech-Text Foundation Models0
Speech Recognition Transformers: Topological-lingualism Perspective0
Speech Recognition using EEG signals recorded using dry electrodes0
Speech Recognition Web Services for Dutch0
Speech Recognition with Augmented Synthesized Speech0
Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning0
Speech Recognition with no speech or with noisy speech0
Speech Recognition With No Speech Or With Noisy Speech Beyond English0
Speech recognition with quaternion neural networks0
Speech Recognition with Quaternion Neural Networks0
Speech Reconstruction from Silent Tongue and Lip Articulation By Pseudo Target Generation and Domain Adversarial Training0
Speech Retrieval-Augmented Generation without Automatic Speech Recognition0
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network0
Speech Summarization using Restricted Self-Attention0
Speech Synthesis as Augmentation for Low-Resource ASR0
Speech Synthesis for Low Resource Languages using Transliteration Enabled Transfer Learning0
Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning0
Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English0
Speech To Semantics: Improve ASR and NLU Jointly via All-Neural Interfaces0
Speech to Speech Translation with Translatotron: A State of the Art Review0
Speech-to-SQL Parsing: Error Correction with Multi-modal Representations0
Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Question0
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation0
Speech to text and text to speech recognition systems-Areview0
Speech Transcription Challenges for Resource Constrained Indigenous Language Cree0
Speech Translation and the End-to-End Promise: Taking Stock of Where We Are0
Speech-T: Transducer for Text to Speech and Beyond0
SpeechVerse: A Large-scale Generalizable Audio Language Model0
SpeechYOLO: Detection and Localization of Speech Objects0
Speed of Light Exact Greedy Decoding for RNN-T Speech Recognition Models on GPU0
Spelling Correction through Rewriting of Non-Autoregressive ASR Lattices0
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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