SOTAVerified

Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

Showing 12011225 of 3012 papers

TitleStatusHype
Predicting Multi-Codebook Vector Quantization Indexes for Knowledge Distillation0
Structured State Space Decoder for Speech Recognition and Synthesis0
An analysis of degenerating speech due to progressive dysarthria on ASR performance0
DiaCorrect: End-to-end error correction for speaker diarizationCode0
FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings0
Blank Collapse: Compressing CTC emission for the faster decodingCode0
DuDe: Dual-Decoder Multilingual ASR for Indian Languages using Common Label Set0
Phonemic Representation and Transcription for Speech to Text Applications for Under-resourced Indigenous African Languages: The Case of Kiswahili0
Filter and evolve: progressive pseudo label refining for semi-supervised automatic speech recognition0
Random Utterance Concatenation Based Data Augmentation for Improving Short-video Speech Recognition0
TRScore: A Novel GPT-based Readability Scorer for ASR Segmentation and Punctuation model evaluation and selection0
Streaming Voice Conversion Via Intermediate Bottleneck Features And Non-streaming Teacher Guidance0
Contextual-Utterance Training for Automatic Speech Recognition0
SAN: a robust end-to-end ASR model architecture0
On Out-of-Distribution Detection for Audio with Deep Nearest NeighborsCode0
V-Cloak: Intelligibility-, Naturalness- & Timbre-Preserving Real-Time Voice Anonymization0
Simulating realistic speech overlaps improves multi-talker ASR0
Exploring Effective Distillation of Self-Supervised Speech Models for Automatic Speech Recognition0
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptationCode0
Make More of Your Data: Minimal Effort Data Augmentation for Automatic Speech Recognition and Translation0
Weight Averaging: A Simple Yet Effective Method to Overcome Catastrophic Forgetting in Automatic Speech Recognition0
Virtuoso: Massive Multilingual Speech-Text Joint Semi-Supervised Learning for Text-To-Speech0
Efficient Utilization of Large Pre-Trained Models for Low Resource ASR0
Reducing Language confusion for Code-switching Speech Recognition with Token-level Language DiarizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1Unverified
2TM-seq2seqTest WER9.7Unverified
3CTC/attentionTest WER8.2Unverified
4LF-MMI TDNNTest WER6.7Unverified
5Whisper-LLaMATest WER6.6Unverified
6End2end ConformerTest WER3.9Unverified
7End2end ConformerTest WER3.7Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7Unverified
9CTC/AttentionTest WER1.5Unverified
10WhisperTest WER1.3Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5Unverified
2CleanMel-L-maskCER14.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32Unverified
2Whisper-largev3-finetunedTest WER10.82Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98Unverified