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 301325 of 3012 papers

TitleStatusHype
Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with AphasiaCode0
Latent Tree Language ModelCode0
A Dataset for Speech Emotion Recognition in Greek Theatrical PlaysCode0
Large-Scale End-to-End Multilingual Speech Recognition and Language Identification with Multi-Task LearningCode0
A Comparative Study on Transformer vs RNN in Speech ApplicationsCode0
An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer LearningCode0
Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative TrainingCode0
Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech RecognitionCode0
Language Complexity and Speech Recognition Accuracy: Orthographic Complexity Hurts, Phonological Complexity Doesn'tCode0
Language Identification Using Deep Convolutional Recurrent Neural NetworksCode0
LASER: Learning by Aligning Self-supervised Representations of Speech for Improving Content-related TasksCode0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic InformationCode0
Iterative Pseudo-Labeling for Speech RecognitionCode0
Intrinsic evaluation of language models for code-switchingCode0
Interpersonal Relationship Labels for the CALLHOME CorpusCode0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptationCode0
Kurdish (Sorani) Speech to Text: Presenting an Experimental DatasetCode0
Analyzing the impact of speaker localization errors on speech separation for automatic speech recognitionCode0
Adapting the adapters for code-switching in multilingual ASRCode0
Analyzing Robustness of End-to-End Neural Models for Automatic Speech RecognitionCode0
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech RecognitionCode0
Instant One-Shot Word-Learning for Context-Specific Neural Sequence-to-Sequence Speech RecognitionCode0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
Show:102550
← PrevPage 13 of 121Next →

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