22 citations · 39 across the 11 of their papers we have counts for
11 papers
Chat2Map: Efficient Scene Mapping from Multi-Ego Conversations
Sagnik Majumder, Hao Jiang, Pierre Moulon +4
Can conversational videos captured from multiple egocentric viewpoints reveal the map of a scene in a cost-efficient way? We seek to answer this question by proposing a new problem…
Towards Improved Room Impulse Response Estimation for Speech Recognition
Anton Ratnarajah, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu +3
We propose a novel approach for blind room impulse response (RIR) estimation systems in the context of a downstream application scenario, far-field automatic speech recognition (AS…
Direct and Residual Subspace Decomposition of Spatial Room Impulse Responses
Thomas Deppisch, Sebastià V. Amengual Garí, Paul Calamia +1
Psychoacoustic experiments have shown that directional properties of the direct sound, salient reflections, and the late reverberation of an acoustic room response can have a disti…
SAQAM: Spatial Audio Quality Assessment Metric
Pranay Manocha, Anurag Kumar, Buye Xu +4
Audio quality assessment is critical for assessing the perceptual realism of sounds. However, the time and expense of obtaining ''gold standard'' human judgments limit the availabi…
SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning
Changan Chen, Carl Schissler, Sanchit Garg +6
We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio rendering for 3D environments. Given a 3D mesh of a real-world environment, SoundSpaces can generate hi…
Visual Acoustic Matching
Changan Chen, Ruohan Gao, Paul Calamia +1
We introduce the visual acoustic matching task, in which an audio clip is transformed to sound like it was recorded in a target environment. Given an image of the target environmen…
Multichannel Speech Enhancement without Beamforming
Asutosh Pandey, Buye Xu, Anurag Kumar +3
Deep neural networks are often coupled with traditional spatial filters, such as MVDR beamformers for effectively exploiting spatial information. Even though single-stage end-to-en…
Time-domain Ad-hoc Array Speech Enhancement Using a Triple-path Network
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
Deep neural networks (DNNs) are very effective for multichannel speech enhancement with fixed array geometries. However, it is not trivial to use DNNs for ad-hoc arrays with unknow…
TPARN: Triple-path Attentive Recurrent Network for Time-domain Multichannel Speech Enhancement
Ashutosh Pandey, Buye Xu, Anurag Kumar +3
In this work, we propose a new model called triple-path attentive recurrent network (TPARN) for multichannel speech enhancement in the time domain. TPARN extends a single-channel d…
Filtered Noise Shaping for Time Domain Room Impulse Response Estimation From Reverberant Speech
Christian J. Steinmetz, Vamsi Krishna Ithapu, Paul Calamia
Deep learning approaches have emerged that aim to transform an audio signal so that it sounds as if it was recorded in the same room as a reference recording, with applications bot…
DPLM: A Deep Perceptual Spatial-Audio Localization Metric
Pranay Manocha, Anurag Kumar, Buye Xu +4
Subjective evaluations are critical for assessing the perceptual realism of sounds in audio-synthesis driven technologies like augmented and virtual reality. However, they are chal…