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Found 18 papers, 2 papers with code
Data-driven Joint Detection and Localization of Acoustic Reflectors
Room geometry inference algorithms rely on the localization of acoustic reflectors to identify boundary surfaces of an enclosure.
Simulating room transfer functions between transducers mounted on audio devices using a modified image source method
The image source method (ISM) is often used to simulate room acoustics due to its ease of use and computational efficiency.
Data-driven 3D Room Geometry Inference with a Linear Loudspeaker Array and a Single Microphone
Motivated by the increasing popularity of commercially available soundbars, this article presents a data-driven 3D RGI method using RIRs measured from a linear loudspeaker array to a single microphone.
Better Together: Dialogue Separation and Voice Activity Detection for Audio Personalization in TV
When dialogue and background sounds are not separately available from the production stage, Dialogue Separation (DS) can estimate them to enable personalization.
Beamformer-Guided Target Speaker Extraction
By allowing for time-varying embeddings in the single-channel TSE block, the proposed method fully exploits the correspondence between the front-end beamformer output and the target speech in the microphone signal.
Multi-Microphone Speaker Separation by Spatial Regions
The network is trained to enforce a fixed mapping of regions to network outputs.
Contrastive Representation Learning for Acoustic Parameter Estimation
A study is presented in which a contrastive learning approach is used to extract low-dimensional representations of the acoustic environment from single-channel, reverberant speech signals.
Audiovisual Database with 360 Video and Higher-Order Ambisonics Audio for Perception, Cognition, Behavior, and QoE Evaluation Research
Research into multi-modal perception, human cognition, behavior, and attention can benefit from high-fidelity content that may recreate real-life-like scenes when rendered on head-mounted displays.
AID: Open-source Anechoic Interferer Dataset
A dataset of anechoic recordings of various sound sources encountered in domestic environments is presented.
Dialogue Enhancement and Listening Effort in Broadcast Audio: A Multimodal Evaluation
A physiological indicator of LE known from audiology studies is pupil size.
Speaker Verification in Multi-Speaker Environments Using Temporal Feature Fusion
Classical speaker verification (SV) approaches estimate a fixed-dimensional embedding from a speech utterance that encodes the speaker's voice characteristics.
AmbiSep: Ambisonic-to-Ambisonic Reverberant Speech Separation Using Transformer Networks
Consider a multichannel Ambisonic recording containing a mixture of several reverberant speech signals.
Blind Reverberation Time Estimation in Dynamic Acoustic Conditions
The estimation of reverberation time from real-world signals plays a central role in a wide range of applications.
New Insights on Target Speaker Extraction
However, such studies have been conducted on a few datasets and have not considered recent deep neural network architectures for SS that have shown impressive separation performance.
Signal-Aware Direction-of-Arrival Estimation Using Attention Mechanisms
The impact of attention on DOA estimators and different training strategies for attention and DOA DNNs are not yet studied in depth.
An Empirical Study of Visual Features for DNN based Audio-Visual Speech Enhancement in Multi-talker Environments
Audio-visual speech enhancement (AVSE) methods use both audio and visual features for the task of speech enhancement and the use of visual features has been shown to be particularly effective in multi-speaker scenarios.
Efficient Training Data Generation for Phase-Based DOA Estimation
By an evaluation using data from measured room impulse responses, we demonstrate that a model trained with the proposed training data generation method performs comparably to models trained with data generated based on the source-image method.
Informed Source Extraction With Application to Acoustic Echo Reduction
Recent deep learning-based methods leverage a speaker discriminative model that maps a reference snippet uttered by the target speaker into a single embedding vector that encapsulates the characteristics of the target speaker.
