20 citations · 27 across the 9 of their papers we have counts for
9 papers
Phoneme-First Prediction for LLM-Based Speech Recognition
Jakob Poncelet, Hugo Van hamme
Recent research has explored integrating Large Language Models (LLMs) with speech encoders to create speech-augmented LLMs capable of contextualized speech recognition. The main ch…
Speech Encoder Fusion for LLM-based Automatic Speech Recognition
Jakob Poncelet, Hugo Van hamme
Speech-aware large language models (LLMs) can incorporate speech through pre-trained acoustic encoders that project speech features into the LLM embedding space. While the choice o…
Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains
Jakob Poncelet, Hugo Van hamme
Speech recognition often fails on rare, domain-specific terms and context-related named entities. Existing contextualization techniques typically bias decoding with keywords or phr…
Leveraging Broadcast Media Subtitle Transcripts for Automatic Speech Recognition and Subtitling
Jakob Poncelet, Hugo Van hamme
The recent advancement of speech recognition technology has been driven by large-scale datasets and attention-based architectures, but many challenges still remain, especially for…
Efficient Extraction of Noise-Robust Discrete Units from Self-Supervised Speech Models
Jakob Poncelet, Yujun Wang, Hugo Van hamme
Continuous speech can be converted into a discrete sequence by deriving discrete units from the hidden features of self-supervised learned (SSL) speech models. Although SSL models…
Unsupervised Accent Adaptation Through Masked Language Model Correction Of Discrete Self-Supervised Speech Units
Jakob Poncelet, Hugo Van hamme
Self-supervised pre-trained speech models have strongly improved speech recognition, yet they are still sensitive to domain shifts and accented or atypical speech. Many of these mo…
Learning to Jointly Transcribe and Subtitle for End-to-End Spontaneous Speech Recognition
Jakob Poncelet, Hugo Van hamme
TV subtitles are a rich source of transcriptions of many types of speech, ranging from read speech in news reports to conversational and spontaneous speech in talk shows and soaps.…
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch
Jakob Poncelet, Hugo Van hamme
Recent research in speech processing exhibits a growing interest in unsupervised and self-supervised representation learning from unlabelled data to alleviate the need for large am…
Multitask Learning with Capsule Networks for Speech-to-Intent Applications
Jakob Poncelet, Hugo Van hamme
Voice controlled applications can be a great aid to society, especially for physically challenged people. However this requires robustness to all kinds of variations in speech. A s…