Strategies for improving low resource speech to text translation relying on pre-trained asr models

S Kesiraju, M Sarvas, T Pavlicek, C Macaire… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper presents techniques and findings for improving the performance of low-resource
speech to text translation (ST). We conducted experiments on both simulated and real-low …

Sentiment Reasoning for Healthcare

KN Nguyen, K Le-Duc, BP Tat, D Le, L Vo-Dang… - arXiv preprint arXiv …, 2024 - arxiv.org
Transparency in AI healthcare decision-making is crucial for building trust among AI and
users. Incorporating reasoning capabilities enables Large Language Models (LLMs) to …

Towards Speech Dialogue Translation Mediating Speakers of Different Languages

S Shimizu, C Chu, S Li, S Kurohashi - arXiv preprint arXiv:2305.09210, 2023 - arxiv.org
We present a new task, speech dialogue translation mediating speakers of different
languages. We construct the SpeechBSD dataset for the task and conduct baseline …

Attention-based End-to-End Models in Language Technology

A Rouhe - 2024 - aaltodoc.aalto.fi
Speech recognition specifically, and language technology more generally, have started to
find everyday use. Challenging language tasks have become feasible through a continued …

[PDF][PDF] Language modeling and machine translation: improvements in training and modeling

G Yingbo - www-i6.informatik.rwth-aachen.de
The field of statistical language modeling and machine translation has seen rapid
developments in recent years, with artificial neural networks taking center of the stage …