activity
20222026
most citedPixIT: Joint Training of Speaker Diarization and Speech Separation from Real-world Multi-speaker Recordings

15 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2026

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…

cs.SD2025

Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models

Sandipana Dowerah, Atharva Kulkarni, Ajinkya Kulkarni +7

Parallel to the development of advanced deepfake audio generation, audio deepfake detection has also seen significant progress. However, a standardized and comprehensive benchmark…

eess.AS2024

TalTech-IRIT-LIS Speaker and Language Diarization Systems for DISPLACE 2024

Joonas Kalda, Tanel Alumäe, Martin Lebourdais +3

This paper describes the submissions of team TalTech-IRIT-LIS to the DISPLACE 2024 challenge. Our team participated in the speaker diarization and language diarization tracks of th…

eess.AS2024★ 15 cited

PixIT: Joint Training of Speaker Diarization and Speech Separation from Real-world Multi-speaker Recordings

Joonas Kalda, Clément Pagés, Ricard Marxer +2

A major drawback of supervised speech separation (SSep) systems is their reliance on synthetic data, leading to poor real-world generalization. Mixture invariant training (MixIT) w…

eess.AS2022

Collar-aware Training for Streaming Speaker Change Detection in Broadcast Speech

Joonas Kalda, Tanel Alumäe

In this paper, we present a novel training method for speaker change detection models. Speaker change detection is often viewed as a binary sequence labelling problem. The main cha…