812 citations · 912 across the 18 of their papers we have counts for
19 papers
NOMAD: Unsupervised Learning of Perceptual Embeddings for Speech Enhancement and Non-matching Reference Audio Quality Assessment
Alessandro Ragano, Jan Skoglund, Andrew Hines
This paper presents NOMAD (Non-Matching Audio Distance), a differentiable perceptual similarity metric that measures the distance of a degraded signal against non-matching referenc…
Reduce, Reuse, Recycle: Is Perturbed Data better than Other Language augmentation for Low Resource Self-Supervised Speech Models
Asad Ullah, Alessandro Ragano, Andrew Hines
Self-supervised representation learning (SSRL) has demonstrated superior performance than supervised models for tasks including phoneme recognition. Training SSRL models poses a ch…
Exploring the Impact of Noise and Degradations on Heart Sound Classification Models
Davoud Shariat Panah, Andrew Hines, Susan McKeever
The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart s…
Learning Music Representations with wav2vec 2.0
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Learning music representations that are general-purpose offers the flexibility to finetune several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation mo…
Using Rater and System Metadata to Explain Variance in the VoiceMOS Challenge 2022 Dataset
Michael Chinen, Jan Skoglund, Chandan K A Reddy +2
Non-reference speech quality models are important for a growing number of applications. The VoiceMOS 2022 challenge provided a dataset of synthetic voice conversion and text-to-spe…
Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction
Helard Becerra, Alessandro Ragano, Andrew Hines
Recent studies have shown how self-supervised models can produce accurate speech quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 model allows c…
A Comparison of Deep Learning MOS Predictors for Speech Synthesis Quality
Alessandro Ragano, Emmanouil Benetos, Michael Chinen +4
Speech synthesis quality prediction has made remarkable progress with the development of supervised and self-supervised learning (SSL) MOS predictors but some aspects related to th…
Supervised Learning based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Study
Arslan Ahmad, Atif Bin Mansoor, Alcardo Alex Barakabitze +3
The Quality of Experience (QoE) based service management remains key for successful provisioning of multimedia services in next-generation networks such as 5G/6G, which requires pr…
AQP: An Open Modular Python Platform for Objective Speech and Audio Quality Metrics
Jack Geraghty, Jiazheng Li, Alessandro Ragano +1
Audio quality assessment has been widely researched in the signal processing area. Full-reference objective metrics (e.g., POLQA, ViSQOL) have been developed to estimate the audio…
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Non-intrusive speech quality assessment is a crucial operation in multimedia applications. The scarcity of annotated data and the lack of a reference signal represent some of the m…
WARP-Q: Quality Prediction For Generative Neural Speech Codecs
Wissam A. Jassim, Jan Skoglund, Michael Chinen +1
Good speech quality has been achieved using waveform matching and parametric reconstruction coders. Recently developed very low bit rate generative codecs can reconstruct high qual…
ViSQOL v3: An Open Source Production Ready Objective Speech and Audio Metric
Michael Chinen, Felicia S. C. Lim, Jan Skoglund +3
Estimation of perceptual quality in audio and speech is possible using a variety of methods. The combined v3 release of ViSQOL and ViSQOLAudio (for speech and audio, respectively,)…
How Crisp is the Crease? A Subjective Study on Web Browsing Perception of Above-The-Fold
Hamed Z. Jahromi, Declan T. Delaney, Andrew Hines
Quality of Experience (QoE) for various types of websites has gained significant attention in recent years. In order to design and evaluate websites, a metric that can estimate a u…
Speech Quality Factors for Traditional and Neural-Based Low Bit Rate Vocoders
Wissam A. Jassim, Jan Skoglund, Michael Chinen +1
This study compares the performances of different algorithms for coding speech at low bit rates. In addition to widely deployed traditional vocoders, a selection of recently develo…
How deep is your encoder: an analysis of features descriptors for an autoencoder-based audio-visual quality metric
Helard Martinez, Andrew Hines, Mylene C. Q. Farias
The development of audio-visual quality assessment models poses a number of challenges in order to obtain accurate predictions. One of these challenges is the modelling of the comp…
You Drive Me Crazy! Interactive QoE Assessment for Telepresence Robot Control
Hamed Z. Jahromi, Ivan Bartolec, Edwin Gamboa +2
Telepresence robots (TPRs) are versatile, remotely controlled vehicles that enable physical presence and human-to-human interaction over a distance. Thanks to improving hardware an…
Audio Impairment Recognition Using a Correlation-Based Feature Representation
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks t…
NAViDAd: A No-Reference Audio-Visual Quality Metric Based on a Deep Autoencoder
Helard Martinez, M. C. Farias, A. Hines
The development of models for quality prediction of both audio and video signals is a fairly mature field. But, although several multimodal models have been proposed, the area of a…
5G network slicing using SDN and NFV- A survey of taxonomy, architectures and future challenges
Alcardo Alex Barakabitze, Arslan Ahmad, Rashid Mijumbi +1
In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirem…