14 citations · 20 across the 16 of their papers we have counts for
16 papers
Systematic Evaluation of Time-Frequency Features for Binaural Sound Source Localization
Davoud Shariat Panah, Alessandro Ragano, Dan Barry +2
This study presents a systematic evaluation of time-frequency feature design for binaural sound source localization (SSL), focusing on how feature selection influences model perfor…
Binaspect -- A Python Library for Binaural Audio Analysis, Visualization & Feature Generation
Dan Barry, Davoud Shariat Panah, Alessandro Ragano +2
We present Binaspect, an open-source Python library for binaural audio analysis, visualization, and feature generation. Binaspect generates interpretable "azimuth maps" by calculat…
Binamix -- A Python Library for Generating Binaural Audio Datasets
Dan Barry, Davoud Shariat Panah, Alessandro Ragano +2
The increasing demand for spatial audio in applications such as virtual reality, immersive media, and spatial audio research necessitates robust solutions to generate binaural audi…
BINAQUAL: A Full-Reference Objective Localization Similarity Metric for Binaural Audio
Davoud Shariat Panah, Dan Barry, Alessandro Ragano +2
Spatial audio enhances immersion in applications such as virtual reality, augmented reality, gaming, and cinema by creating a three-dimensional auditory experience. Ensuring the sp…
Beyond Correlation: Evaluating Multimedia Quality Models with the Constrained Concordance Index
Alessandro Ragano, Helard Becerra Martinez, Andrew Hines
This study investigates the evaluation of multimedia quality models, focusing on the inherent uncertainties in subjective Mean Opinion Score (MOS) ratings due to factors like rater…
SCOREQ: Speech Quality Assessment with Contrastive Regression
Alessandro Ragano, Jan Skoglund, Andrew Hines
In this paper, we present SCOREQ, a novel approach for speech quality prediction. SCOREQ is a triplet loss function for contrastive regression that addresses the domain generalisat…
Dialogue Understandability: Why are we streaming movies with subtitles?
Helard Becerra Martinez, Alessandro Ragano, Diptasree Debnath +4
Watching movies and TV shows with subtitles enabled is not simply down to audibility or speech intelligibility. A variety of evolving factors related to technological advances, cin…
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…
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…
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…
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…