1 citations · 1 across the 5 of their papers we have counts for
7 papers
MICRO: Multi-Fidelity Active Search for Severe Error Discovery
Orlando Leone, Niclas Pokel, Pehuén Moure +2
Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decide which items to annotate. We…
Demonstration of Adapt4Me: An Uncertainty-Aware Authoring Environment for Personalizing Automatic Speech Recognition to Non-normative Speech
Niclas Pokel, Yiming Zhao, Pehuén Moure +2
Personalizing Automatic Speech Recognition (ASR) for non-normative speech remains challenging because data collection is labor-intensive and model training is technically complex.…
Group Relative Policy Optimization for Text-to-Speech with Large Language Models
Chang Liu, Ya-Jun Hu, Ying-Ying Gao +2
This paper proposes a GRPO-based approach to enhance the performance of large language model (LLM)-based text-to-speech (TTS) models by deriving rewards from an off-the-shelf autom…
Variational Low-Rank Adaptation for Personalized Impaired Speech Recognition
Niclas Pokel, Pehuén Moure, Roman Boehringer +2
Speech impairments resulting from congenital disorders, such as cerebral palsy, down syndrome, or apert syndrome, as well as acquired brain injuries due to stroke, traumatic accide…
Data-Efficient ASR Personalization for Non-Normative Speech Using an Uncertainty-Based Phoneme Difficulty Score for Guided Sampling
Niclas Pokel, Pehuén Moure, Roman Böhringer +1
ASR systems struggle with non-normative speech due to high acoustic variability and data scarcity. We propose a data-efficient method using phoneme-level uncertainty to guide fine-…
Adapting Foundation Speech Recognition Models to Impaired Speech: A Semantic Re-chaining Approach for Personalization of German Speech
Niclas Pokel, Pehuén Moure, Roman Boehringer +1
Speech impairments caused by conditions such as cerebral palsy or genetic disorders pose significant challenges for automatic speech recognition (ASR) systems. Despite recent advan…
Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System
Weizhou Shen, Yingqi Gao, Canbin Huang +3
Developing an efficient retriever to retrieve knowledge from a large-scale knowledge base (KB) is critical for task-oriented dialogue systems to effectively handle localized and sp…