Espnet-slu: Advancing spoken language understanding through espnet
As Automatic Speech Processing (ASR) systems are getting better, there is an increasing
interest of using the ASR output to do downstream Natural Language Processing (NLP) …
interest of using the ASR output to do downstream Natural Language Processing (NLP) …
MARS: Mixed virtual and real wearable sensors for human activity recognition with multidomain deep learning model
Together with the rapid development of the Internet of Things, human activity recognition
(HAR) using wearable inertial measurement units (IMUs) becomes a promising technology …
(HAR) using wearable inertial measurement units (IMUs) becomes a promising technology …
Endangered Languages are not Low-Resourced!
M Hämäläinen - arxiv preprint arxiv:2103.09567, 2021 - arxiv.org
The term low-resourced has been tossed around in the field of natural language processing
to a degree that almost any language that is not English can be called" low-resourced"; …
to a degree that almost any language that is not English can be called" low-resourced"; …
Survey on publicly available sinhala natural language processing tools and research
N De Silva - arxiv preprint arxiv:1906.02358, 2019 - arxiv.org
Sinhala is the native language of the Sinhalese people who make up the largest ethnic
group of Sri Lanka. The language belongs to the globe-spanning language tree, Indo …
group of Sri Lanka. The language belongs to the globe-spanning language tree, Indo …
Improving end-to-end speech-to-intent classification with reptile
End-to-end spoken language understanding (SLU) systems have many advantages over
conventional pipeline systems, but collecting in-domain speech data to train an end-to-end …
conventional pipeline systems, but collecting in-domain speech data to train an end-to-end …
A quantum kernel learning approach to acoustic modeling for spoken command recognition
We propose a quantum kernel learning (QKL) framework to address the inherent data
sparsity issues often encountered in training large-scare acoustic models in low-resource …
sparsity issues often encountered in training large-scare acoustic models in low-resource …
On building spoken language understanding systems for low resourced languages
A Gupta - arxiv preprint arxiv:2205.12818, 2022 - arxiv.org
Spoken dialog systems are slowly becoming and integral part of the human experience due
to their various advantages over textual interfaces. Spoken language understanding (SLU) …
to their various advantages over textual interfaces. Spoken language understanding (SLU) …
Sinhala and tamil speech intent identification from english phoneme based asr
Today we can find many use cases for content-based speech classification. These include
speech topic identification and spoken command recognition. Automatic Speech …
speech topic identification and spoken command recognition. Automatic Speech …
Acoustics based intent recognition using discovered phonetic units for low resource languages
With recent advancements in language technologies, humans are now speaking to devices.
Increasing the reach of spoken language technologies requires building systems in local …
Increasing the reach of spoken language technologies requires building systems in local …
Low resource multi-asr speech command recognition
I Mohamed, U Thayasivam - 2022 Moratuwa Engineering …, 2022 - ieeexplore.ieee.org
There are several applications when comes to spoken language understanding (SLU) such
as topic identification and intent detection. One of the primary underlying components used …
as topic identification and intent detection. One of the primary underlying components used …