49 citations · 99 across the 30 of their papers we have counts for
6 papers · 1 filter
Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues
Norbert Braunschweiler, Rama Doddipatla, Simon Keizer +1
In this paper, we investigate the use of large language models (LLMs) like ChatGPT for document-grounded response generation in the context of information-seeking dialogues. For ev…
Adversarial learning of neural user simulators for dialogue policy optimisation
Simon Keizer, Caroline Dockes, Norbert Braunschweiler +2
Reinforcement learning based dialogue policies are typically trained in interaction with a user simulator. To obtain an effective and robust policy, this simulator should generate…
A Teacher-Student approach for extracting informative speaker embeddings from speech mixtures
Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2
We introduce a monaural neural speaker embeddings extractor that computes an embedding for each speaker present in a speech mixture. To allow for supervised training, a teacher-stu…
Frame-wise and overlap-robust speaker embeddings for meeting diarization
Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2
Using a Teacher-Student training approach we developed a speaker embedding extraction system that outputs embeddings at frame rate. Given this high temporal resolution and the fact…
Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition
Mohan Li, Rama Doddipatla, Catalin Zorila
This paper proposes a self-regularised minimum latency training (SR-MLT) method for streaming Transformer-based automatic speech recognition (ASR) systems. In previous works, laten…
Non-autoregressive End-to-end Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding
Mohan Li, Rama Doddipatla
This paper presents the use of non-autoregressive (NAR) approaches for joint automatic speech recognition (ASR) and spoken language understanding (SLU) tasks. The proposed NAR syst…