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Found 9 papers, 1 papers with code
Multi-Perspective Document Revision
To model the task, we design a novel Japanese multi-perspective document revision dataset that simultaneously handles seven perspectives to improve the readability and clarity of a document.
On the Use of Modality-Specific Large-Scale Pre-Trained Encoders for Multimodal Sentiment Analysis
This paper investigates the effectiveness and implementation of modality-specific large-scale pre-trained encoders for multimodal sentiment analysis~(MSA).
Streaming Target-Speaker ASR with Neural Transducer
We confirm in experiments that our TS-ASR achieves comparable recognition performance with conventional cascade systems in the offline setting, while reducing computation costs and realizing streaming TS-ASR.
Strategies to Improve Robustness of Target Speech Extraction to Enrollment Variations
Experimental validation reveals the effectiveness of both worst-enrollment target training and SI-loss training to improve robustness against enrollment variations, by increasing speaker discriminability.
Listen only to me! How well can target speech extraction handle false alarms?
Target speech extraction (TSE) extracts the speech of a target speaker in a mixture given auxiliary clues characterizing the speaker, such as an enrollment utterance.
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR
The artifact component is defined as the SE error signal that cannot be represented as a linear combination of speech and noise sources.
Learning to Enhance or Not: Neural Network-Based Switching of Enhanced and Observed Signals for Overlapping Speech Recognition
To mitigate the degradation, we introduced a rule-based method to switch the ASR input between the enhanced and observed signals, which showed promising results.
Should We Always Separate?: Switching Between Enhanced and Observed Signals for Overlapping Speech Recognition
', we analyze ASR performance on observed and enhanced speech at various noise and interference conditions, and show that speech enhancement degrades ASR under some conditions even for overlapping speech.
Multimodal Attention Fusion for Target Speaker Extraction
Recently an audio-visual target speaker extraction has been proposed that extracts target speech by using complementary audio and visual clues.
