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Found 10 papers, 1 papers with code
NTT Multi-Speaker ASR System for the DASR Task of CHiME-8 Challenge
We present a distant automatic speech recognition (DASR) system developed for the CHiME-8 DASR track.
Recursive Attentive Pooling for Extracting Speaker Embeddings from Multi-Speaker Recordings
This paper proposes a method for extracting speaker embedding for each speaker from a variable-length recording containing multiple speakers.
SpeakerBeam-SS: Real-time Target Speaker Extraction with Lightweight Conv-TasNet and State Space Modeling
Real-time target speaker extraction (TSE) is intended to extract the desired speaker's voice from the observed mixture of multiple speakers in a streaming manner.
Factor-Conditioned Speaking-Style Captioning
We also propose greedy-then-sampling (GtS) decoding, which first predicts speaking-style factors deterministically to guarantee semantic accuracy, and then generates a caption based on factor-conditioned sampling to ensure diversity.
Speech Rhythm-Based Speaker Embeddings Extraction from Phonemes and Phoneme Duration for Multi-Speaker Speech Synthesis
This paper proposes a speech rhythm-based method for speaker embeddings to model phoneme duration using a few utterances by the target speaker.
NTT speaker diarization system for CHiME-7: multi-domain, multi-microphone End-to-end and vector clustering diarization
This paper details our speaker diarization system designed for multi-domain, multi-microphone casual conversations.
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff
This paper addresses the tradeoff between standard accuracy on clean examples and robustness against adversarial examples in deep neural networks (DNNs).
End-to-End Joint Target and Non-Target Speakers ASR
Target-speaker ASR systems are a promising way to only transcribe a target speaker's speech by enrolling the target speaker's information.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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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).
Neural Dialogue Context Online End-of-Turn Detection
This paper proposes a fully neural network based dialogue-context online end-of-turn detection method that can utilize long-range interactive information extracted from both speaker{'}s utterances and collocutor{'}s utterances.
