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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

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Showing 1826–1850 of 3012 papers

TitleStatusHype
Sequence-level Confidence Classifier for ASR Utterance Accuracy and Application to Acoustic Models—0
On joint training with interfaces for spoken language understanding—0
Rethinking End-to-End Evaluation of Decomposable Tasks: A Case Study on Spoken Language Understanding—0
QASR: QCRI Aljazeera Speech Resource -- A Large Scale Annotated Arabic Speech Corpus—0
Where are we in semantic concept extraction for Spoken Language Understanding?—0
Zero-Shot Joint Modeling of Multiple Spoken-Text-Style Conversion Tasks using Switching Tokens—0
Mixtures of Deep Neural Experts for Automated Speech Scoring—0
A Discriminative Entity-Aware Language Model for Virtual Assistants—0
On-Device Personalization of Automatic Speech Recognition Models for Disordered Speech—0
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System—0
An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition—0
Layer Pruning on Demand with Intermediate CTC—0
Multi-mode Transformer Transducer with Stochastic Future Context—0
Multi-Speaker ASR Combining Non-Autoregressive Conformer CTC and Conditional Speaker ChainCode0
Topic Classification on Spoken Documents Using Deep Acoustic and Linguistic Features—0
Momentum Pseudo-Labeling for Semi-Supervised Speech RecognitionCode0
Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget—0
Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft's Submission to SwissText 2021—0
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech—0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling—0
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts—0
Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition—0
Assessing the Use of Prosody in Constituency Parsing of Imperfect TranscriptsCode0
SynthASR: Unlocking Synthetic Data for Speech Recognition—0
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition—0
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All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

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