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Found 17 papers, 11 papers with code
A Generalized Bandsplit Neural Network for Cinematic Audio Source Separation
Cinematic audio source separation is a relatively new subtask of audio source separation, with the aim of extracting the dialogue, music, and effects stems from their mixture.
Preliminary investigation of the short-term in situ performance of an automatic masker selection system
Soundscape augmentation or "masking" introduces wanted sounds into the acoustic environment to improve acoustic comfort.
Quantifying Spatial Audio Quality Impairment
Spatial audio quality is a highly multifaceted concept, with many interactions between environmental, geometrical, anatomical, psychological, and contextual considerations.
Assessment of a cost-effective headphone calibration procedure for soundscape evaluations
To increase the availability and adoption of the soundscape standard, a low-cost calibration procedure for reproduction of audio stimuli over headphones was proposed as part of the global ``Soundscape Attributes Translation Project'' (SATP) for validating ISO/TS~12913-2:2018 perceived affective quality (PAQ) attribute translations.
Do uHear? Validation of uHear App for Preliminary Screening of Hearing Ability in Soundscape Studies
Hence, in this study, we investigate the effectiveness of the uHear app, an iOS application, as an affordable and automatic alternative to a conventional audiometer in screening participants for hearing loss for the purpose of soundscape studies or listening tests in general.
Singapore Soundscape Site Selection Survey (S5): Identification of Characteristic Soundscapes of Singapore via Weighted k-means Clustering
We then performed weighted k-means clustering on the selected locations, with weights for each location derived from previous frequencies and durations spent in each location by each participant.
Preliminary assessment of a cost-effective headphone calibration procedure for soundscape evaluations
Preliminary experiments found that calibration with the OCV method differed significantly from the reference binaural recordings in sound pressure levels, whereas negligible differences in levels were observed with the HATS calibration.
Autonomous In-Situ Soundscape Augmentation via Joint Selection of Masker and Gain
The selection of maskers and playback gain levels in a soundscape augmentation system is crucial to its effectiveness in improving the overall acoustic comfort of a given environment.
Deployment of an IoT System for Adaptive In-Situ Soundscape Augmentation
Soundscape augmentation is an emerging approach for noise mitigation by introducing additional sounds known as "maskers" to increase acoustic comfort.
Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models
Latte (for LATent Tensor Evaluation) is a Python library for evaluation of latent-based generative models in the fields of disentanglement learning and controllable generation.
SALSA-Lite: A Fast and Effective Feature for Polyphonic Sound Event Localization and Detection with Microphone Arrays
In this work, we introduce SALSA-Lite, a fast and effective feature for polyphonic SELD using microphone array inputs.
AVASpeech-SMAD: A Strongly Labelled Speech and Music Activity Detection Dataset with Label Co-Occurrence
We propose a dataset, AVASpeech-SMAD, to assist speech and music activity detection research.
Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes
Controllable music generation with deep generative models has become increasingly reliant on disentanglement learning techniques.
End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression
We also propose a dual-mask technique for joint echo and noise suppression with simultaneous speech enhancement.
SALSA: Spatial Cue-Augmented Log-Spectrogram Features for Polyphonic Sound Event Localization and Detection
Sound event localization and detection (SELD) consists of two subtasks, which are sound event detection and direction-of-arrival estimation.
Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sørensen-Dice Coefficient Loss and Transfer Learning
The S{\o}rensen--Dice Coefficient has recently seen rising popularity as a loss function (also known as Dice loss) due to its robustness in tasks where the number of negative samples significantly exceeds that of positive samples, such as semantic segmentation, natural language processing, and sound event detection.
What Makes Sound Event Localization and Detection Difficult? Insights from Error Analysis
Sound event localization and detection (SELD) is an emerging research topic that aims to unify the tasks of sound event detection and direction-of-arrival estimation.
