Long documents such as academic articles and business reports have been the standard
format to detail out important issues and complicated subjects that require extra attention. An …

Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …

Meetings are a key component of human collaboration. As increasing numbers of meetings
are recorded and transcribed, meeting summaries have become essential to remind those …

The objective of this work is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …

Argument mining is the automatic identification and extraction of the structure of inference
and reasoning expressed as arguments presented in natural language. Understanding …

Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the
6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge …

In recent years, wsj0-2mix has become the reference dataset for single-channel speech
separation. Most deep learning-based speech separation models today are benchmarked …

Most existing datasets for speaker identification contain samples obtained under quite
constrained conditions, and are usually hand-annotated, hence limited in size. The goal of …

Spoken Language Understanding infers semantic meaning directly from audio data, and
thus promises to reduce error propagation and misunderstandings in end-user applications …

Dialogue is an essential part of human communication and cooperation. Existing research
mainly focuses on short dialogue scenarios in a one-on-one fashion. However, multi-person …