This study introduces a novel training paradigm, audio difference learni...
End-to-end neural diarization (EEND) with encoder-decoder-based attracto...
This paper proposes a method for improved CTC inference with searched
in...
End-to-end automatic speech recognition (ASR) directly maps input speech...
This paper proposes InterAug: a novel training method for CTC-based ASR ...
This paper investigates an end-to-end neural diarization (EEND) method f...
In this paper, we present a semi-supervised training technique using
pse...
In this paper, we present a conditional multitask learning method for
en...
This paper provides a detailed description of the Hitachi-JHU system tha...
This paper proposes an online end-to-end diarization that can handle
ove...
This paper investigates the utilization of an end-to-end diarization mod...
We propose a block-online algorithm of guided source separation (GSS). G...
A novel framework for meeting transcription using asynchronous microphon...
Neural sequence-to-sequence models are well established for applications...
Speech separation has been extensively explored to tackle the cocktail p...
End-to-end speaker diarization using a fully supervised self-attention
m...
Speaker diarization is an essential step for processing multi-speaker au...
End-to-end speaker diarization for an unknown number of speakers is addr...
The most common approach to speaker diarization is clustering of speaker...
Speaker diarization is an important pre-processing step for many speech
...
This paper investigates the use of target-speaker automatic speech
recog...
Speaker diarization has been mainly developed based on the clustering of...
In this paper, we propose a novel end-to-end neural-network-based speake...
In this paper, we propose a novel auxiliary loss function for target-spe...
In this paper, we present Hitachi and Paderborn University's joint effor...