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Found 18 papers, 2 papers with code
Cross-Speaker Encoding Network for Multi-Talker Speech Recognition
To the best of our knowledge, this work represents an early effort to integrate SIMO and SISO for multi-talker speech recognition.
Audio-visual End-to-end Multi-channel Speech Separation, Dereverberation and Recognition
Accurate recognition of cocktail party speech containing overlapping speakers, noise and reverberation remains a highly challenging task to date.
Factorised Speaker-environment Adaptive Training of Conformer Speech Recognition Systems
Rich sources of variability in natural speech present significant challenges to current data intensive speech recognition technologies.
Towards Effective and Compact Contextual Representation for Conformer Transducer Speech Recognition Systems
Current ASR systems are mainly trained and evaluated at the utterance level.
Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator
Extending on this, we incorporate a diarization branch into the Sidecar, allowing for unified modeling of both ASR and diarization with a negligible overhead of only 768 parameters.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Use of Speech Impairment Severity for Dysarthric Speech Recognition
A key challenge in dysarthric speech recognition is the speaker-level diversity attributed to both speaker-identity associated factors such as gender, and speech impairment severity.
Exploring Self-supervised Pre-trained ASR Models For Dysarthric and Elderly Speech Recognition
Experiments conducted on the UASpeech dysarthric and DementiaBank Pitt elderly speech corpora suggest TDNN and Conformer ASR systems integrated domain adapted wav2vec2. 0 models consistently outperform the standalone wav2vec2. 0 models by statistically significant WER reductions of 8. 22% and 3. 43% absolute (26. 71% and 15. 88% relative) on the two tasks respectively.
A Sidecar Separator Can Convert a Single-Talker Speech Recognition System to a Multi-Talker One
Although automatic speech recognition (ASR) can perform well in common non-overlapping environments, sustaining performance in multi-talker overlapping speech recognition remains challenging.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Confidence Score Based Speaker Adaptation of Conformer Speech Recognition Systems
Practical application of unsupervised model-based speaker adaptation techniques to data intensive end-to-end ASR systems is hindered by the scarcity of speaker-level data and performance sensitivity to transcription errors.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Confidence Score Based Conformer Speaker Adaptation for Speech Recognition
A key challenge for automatic speech recognition (ASR) systems is to model the speaker level variability.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care to delay further progression.
Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systems
Fundamental modelling differences between hybrid and end-to-end (E2E) automatic speech recognition (ASR) systems create large diversity and complementarity among them.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems designed for normal speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems for normal speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Recent Progress in the CUHK Dysarthric Speech Recognition System
Despite the rapid progress of automatic speech recognition (ASR) technologies in the past few decades, recognition of disordered speech remains a highly challenging task to date.
Audio-Visual Speech Recognition
Automatic Speech Recognition
+4
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks
State-of-the-art automatic speech recognition (ASR) system development is data and computation intensive.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
TopicRefine: Joint Topic Prediction and Dialogue Response Generation for Multi-turn End-to-End Dialogue System
A multi-turn dialogue always follows a specific topic thread, and topic shift at the discourse level occurs naturally as the conversation progresses, necessitating the model's ability to capture different topics and generate topic-aware responses.
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks
Deep neural networks (DNNs) based automatic speech recognition (ASR) systems are often designed using expert knowledge and empirical evaluation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
