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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 601–625 of 3012 papers

TitleStatusHype
A GEN AI Framework for Medical Note Generation—0
ASR-based Features for Emotion Recognition: A Transfer Learning Approach—0
Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition—0
AccentFold: A Journey through African Accents for Zero-Shot ASR Adaptation to Target Accents—0
Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio—0
ASR-based CALL systems and learner speech data: new resources and opportunities for research and development in second language learning—0
ASR-Aware End-to-end Neural Diarization—0
AGADIR: Towards Array-Geometry Agnostic Directional Speech Recognition—0
ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition—0
Automatic Speech Recognition Advancements for Indigenous Languages of the Americas—0
Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond—0
Acoustic and Textual Data Augmentation for Improved ASR of Code-Switching Speech—0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling—0
A Speech Test Set of Practice Business Presentations with Additional Relevant Texts—0
AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR—0
Ask2Mask: Guided Data Selection for Masked Speech Modeling—0
AfriNames: Most ASR models "butcher" African Names—0
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition—0
Clinical BERTScore: An Improved Measure of Automatic Speech Recognition Performance in Clinical Settings—0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data—0
A Corpus of Read and Spontaneous Upper Saxon German Speech for ASR Evaluation—0
A Semi-Automated Live Interlingual Communication Workflow Featuring Intralingual Respeaking: Evaluation and Benchmarking—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
Accented Speech Recognition Inspired by Human Perception—0
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic Speech—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