Small footprint model for noisy far-field keyword spotting
Building a small memory footprint keyword spotting model is important as it typically runs on mobile devices with low computational resources. However, it is very challenging to develop a lightweight model and also maintaining a state-of-the-art result under noisy far field environment. In real l...
Saved in:
Main Author: | Pang, Jin Hui |
---|---|
Other Authors: | Chng Eng Siong |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/158398 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
A new confidence measure combining hidden Markov models and artificial neural networks of phonemes for effective keyword spotting
by: Leow, Su Jun., et al.
Published: (2013) -
Optimising superoscillatory spots for far-field super-resolution imaging
by: Rogers, Katrine S., et al.
Published: (2019) -
Keyword-guided neural conversational model
by: Zhong, Peixiang, et al.
Published: (2021) -
A small vocabulary automatic Filipino speech profanity suppression system using hybrid hidden Markov model/artificial neural network (HMM/ANN) keyword spotting framework
by: Ablaza, Fernando I., et al.
Published: (2014) -
A fast keyword-spotting technique
by: Li, L., et al.
Published: (2013)