37 citations · 37 across the 5 of their papers we have counts for
5 papers
Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization
Yanis Labrak, David Grünert, Séverin Baroudi +11
Long-context audio reasoning is underserved in both training data and evaluation. Existing benchmarks target short-context tasks, and the open-ended generation tasks most relevant…
DASHA: Diarization-Aware Speech-LLM ASR for Healthcare in Code-Switched Indic Doctor-Patient Conversations
Séverin Baroudi, Yanis Labrak, Shashi Kumar +7
Extracting patients' medical conditions from recorded primary-care conversations requires knowing who said what, which is difficult when speech is far-field, spontaneous, overlappi…
Extracting textual overlays from social media videos using neural networks
Adam Słucki, Tomasz Trzcinski, Adam Bielski +1
Textual overlays are often used in social media videos as people who watch them without the sound would otherwise miss essential information conveyed in the audio stream. This is w…
SocialML: machine learning for social media video creators
Tomasz Trzcinski, Adam Bielski, Paweł Cyrta +1
In the recent years, social media have become one of the main places where creative content is being published and consumed by billions of users. Contrary to traditional media, soc…
Speaker Diarization using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings
Pawel Cyrta, Tomasz Trzciński, Wojciech Stokowiec
In this paper we propose a new method of speaker diarization that employs a deep learning architecture to learn speaker embeddings. In contrast to the traditional approaches that b…