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Slides from Lukáš Burget's and Alex Polok's tutorial on Robust speech recognition II.

For more info: https://jsalt2025.fit.vut.cz/summer-school#day7morning

[slides] Day 7 afternoon - JSALT 2025 - Burget, Polok: Robust speech recognition II.

Tutorial held by Lukas Burget [Brno University of Technology] and Alexander Polok [Brno University of Technology]

The afternoon part of the tutorial will include:
1) Introduction to diarization conditioned Whisper (DiCoW) target speaker ASR method (Lukas Burget) (20 min)
2) Lab on target speaker ASR (Alexander Polok) (2 h)

Bio: Alexander Polok is a Junior Researcher and PhD student at the Faculty of Information Technology, Brno University of Technology (BUT). His research focuses on speech recognition, with an emphasis on practical and efficient methods for applying ASR models in conversational settings. His work has received several honors, including the Brno PhD Talent Scholarship, the Jury Award for CHiME Task 2: NOTSOFAR, recognition at IT SPY 2023 for one of the best diploma theses, and a nomination for the Government Award for Talented Students. He also participated in the JSALT 2023 workshop.

For more info visit: https://jsalt2025.fit.vut.cz/

[camera] Day 7 afternoon - JSALT 2025 - Burget, Polok: Robust speech recognition II.

The seventh day of JSALT Summer School 2025 will start with a tutorial held by the workshop research group: End-to-end multi channel multi talker ASR (EMMA), given by Lukas Burget (Brno University of Technology), Samuele Cornell (Carnegie Mellon University), Yoshiki Masuyama (Mitsubishi Electric Research Laboratories).

While ASR achieves superhuman performance on clean benchmarks, it struggles in real-world scenarios like meeting transcription, where word error rates exceed 35% versus under 3% on clean data. This lecture examines the challenges of robust ASR for conversational speech, including noise, reverberation, multiple speakers, and overlapped speech (greater than 15% of meeting duration). The lecture covers evaluation methodologies for long-form multi-speaker audio, including concatenated minimum permutation WER (cpWER), and surveys key datasets from AMI to current benchmarks like CHiME-7/8 and NOTSOFAR1. Technical approaches are categorized into front-end methods (speech separation, beamforming, target speaker extraction) and back-end methods (self-supervised features, serialized output training, target-speaker ASR). Robust ASR remains an active research area with significant opportunities, particularly as large language models enable new applications like automated meeting summarization. Key challenges include speaker tracking, training-inference mismatches, and integrating speech separation, diarization, and recognition components.

For more info visit: https://jsalt2025.fit.vut.cz/summer-school#day6morning

Bio: Lukáš Burget is an associate professor at the Faculty of Information Technology, Brno University of Technology (FIT BUT), and the scientific director of the BUT Speech@FIT group. He is recognized internationally as a leading expert in speech processing. He received his Ph.D. from Brno University of Technology in 2004. From 2000 to 2002, he was a visiting researcher at OGI, Portland, USA, and in 2011–2012, he spent a sabbatical at SRI International in Menlo Park, USA. His research interests include various areas of speech processing, such as acoustic modeling for speech, speaker, and language recognition. He has played a leading role in several JSALT workshops, notably leading the 2008 team that introduced i-vectors, the first widely adopted speech embeddings, and contributing in 2009 to the creation of the widely used Kaldi ASR toolkit. In 2006, he co-founded Phonexia, a company that now employs over 50 full-time staff and delivers speech technologies to clients in more than 60 countries.

Samuele Cornell is currently a postdoctoral research associate at Carnegie Mellon University at the Language Technologies Institute within Prof. Shinji Watanabe research group (WAVLab). He got a doctoral degree in Information Engineering at Università Politecnica delle Marche, Italy in 2023. His research interests are mainly in the area of robust speech processing (speech enhancement, speech separation, diarization, automatic speech recognition) for distant multi-talker conversational scenarios, and also in the broader field of machine listening (sound event detection and classification). He is author and has significant contributions in several popular open-source speech-processing toolkits (e.g. SpeechBrain, ESPNet, Asteroid source separation) and in the organization and co-organization of popular audio processing challenges such as DCASE (Task 4 2022, 2021, 2024), CHiME (CHiME-7/8 DASR lead organizer) and URGENT (2024 and 2025).

Yoshiki Masuyama is a visiting research scientist at Mitsubishi Electric Research Laboratories (MERL) and a collaborator with the Ono Laboratory in the Department of Computer Science, Faculty of Systems Design, Tokyo Metropolitan University. He received his Ph.D. from Tokyo Metropolitan University in 2024. His research interests focus on the integration of signal processing and machine learning technologies for efficient and robust audio processing. He has worked on a wide range of audio signal processing tasks, especially multichannel speech separation, robust automatic speech recognition, and multimodal learning. He is the recipient of the Best Student Paper Award at the IEEE Spoken Language Technology Workshop 2022.

[camera] Day 7 morning - JSALT 2025 - Burget, Cornell, Masuyama: Robust speech recognition I.

Slides from the tutorial given by the EMMA Workshop Group (Burget, Cornell, Masuyama).

For more info visit: https://jsalt2025.fit.vut.cz/end-to-end

[slides] Day 7 morning - JSALT 2025 - Burget, Cornell, Masuyama: Robust speech recognition I.

Jindřich Matoušek [Department of Cybernetics & New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia in Pilsen] will present a brief history, state-of-the-art, and future directions of speech synthesis.
Bio: Jindřich Matoušek is an Associate Professor at the Department of Cybernetics, Faculty of Applied Sciences, University of West Bohemia (UWB) in Pilsen, Czech Republic. He received his M.Sc. and Ph.D. degrees from UWB and has been active as a researcher at the university since 1999, joining the New Technologies for the Information Society (NTIS) research center in 2012. His primary research and teaching interests are computer speech processing, especially speech synthesis. J. Matoušek is the author or co-author of over 180 scientific publications and has served as Area Chair for “Speech Synthesis and Spoken Language Generation” at Interspeech 2021 and 2022 and Publication Chair of Interspeech 2021. He has extensive experience leading and participating in research projects. In 2020, he was on the team awarded the Czech Technology Agency (TAČR) Award for the project “Elimination of the Language Barriers Faced by the Handicapped Viewers of the Czech Television”. For his leadership of the TAČR project “Automatic voice banking and reconstruction for patients after total laryngectomy”, he received the 2020 City of Pilsen Award. J. Matoušek is also active in the scientific community as a member of the evaluation committee for the Antonín Svoboda Award for the best Czech Ph.D. thesis in cybernetics and informatics.

For more info: https://jsalt2025.fit.vut.cz/

[camera] Day 6 afternoon - JSALT 2025 - Matoušek: Speech Synthesis: From Models to Signals and Back

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