Online change detection techniques in time series: An overview
B Namoano, A Starr, C Emmanouilidis… - … on prognostics and …, 2019 - ieeexplore.ieee.org
Time-series change detection has been studied in several fields. From sensor data,
engineering systems, medical diagnosis, and financial markets to user actions on a network …
engineering systems, medical diagnosis, and financial markets to user actions on a network …
Livestock vocalisation classification in farm soundscapes
Livestock vocalisations have been shown to contain information related to animal welfare
and behaviour. Automated sound detection has the potential to facilitate a continuous …
and behaviour. Automated sound detection has the potential to facilitate a continuous …
Music detection from broadcast contents using convolutional neural networks with a Mel-scale kernel
We propose a new method for music detection from broadcasting contents using the
convolutional neural networks with a Mel-scale kernel. In this detection task, music …
convolutional neural networks with a Mel-scale kernel. In this detection task, music …
Speaker embeddings for diarization of broadcast data in the allies challenge
Diarization consists in the segmentation of speech signals and the clustering of
homogeneous speaker segments. State-of-the-art systems typically operate upon speaker …
homogeneous speaker segments. State-of-the-art systems typically operate upon speaker …
Content-based audio classification and retrieval using segmentation, feature extraction and neural network approach
The volume of audio data is increasing tremendously daily on public networks like Internet.
This increases the difficulty in accessing those audio data. Hence, there is a need of efficient …
This increases the difficulty in accessing those audio data. Hence, there is a need of efficient …
Clean vs. overlapped speech-music detection using harmonic-percussive features and multi-task learning
M Bhattacharjee, SRM Prasanna… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
Detection of speech and music signals in isolated and overlapped conditions is an essential
preprocessing step for many audio applications. Speech signals have wavy and continuous …
preprocessing step for many audio applications. Speech signals have wavy and continuous …
3MAS: a multitask, multilabel, multidataset semi-supervised audio segmentation model
When processing audio data, multiple challenges arise, one of them being the diversity of
information present in the audio signal. Various audio segmentation subtasks appeared …
information present in the audio signal. Various audio segmentation subtasks appeared …
Investigating the use of semi-supervised convolutional neural network models for speech/music classification and segmentation
A convolutional neural network architecture, trained with a semi-supervised strategy, is
proposed for speech/music classification (SMC) and segmentation (SMS). It is compared to …
proposed for speech/music classification (SMC) and segmentation (SMS). It is compared to …
Albayzin 2016 spoken term detection evaluation: an international open competitive evaluation in spanish
J Tejedor, DT Toledano, P Lopez-Otero… - EURASIP Journal on …, 2017 - Springer
Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech
repository given a textual representation of a search term. This paper presents an …
repository given a textual representation of a search term. This paper presents an …
[HTML][HTML] An efficient approach for segmentation, feature extraction and classification of audio signals
M Arumugam, M Kaliappan - Circuits and Systems, 2016 - scirp.org
Due to the presence of non-stationarities and discontinuities in the audio signal,
segmentation and classification of audio signal is a really challenging task. Automatic music …
segmentation and classification of audio signal is a really challenging task. Automatic music …