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Found 25 papers, 4 papers with code
End-to-End Multi-Microphone Speaker Extraction Using Relative Transfer Functions
This paper introduces a multi-microphone method for extracting a desired speaker from a mixture involving multiple speakers and directional noise in a reverberant environment.
Explainable DNN-based Beamformer with Postfilter
This paper introduces an explainable DNN-based beamformer with a postfilter (ExNet-BF+PF) for multichannel signal processing.
Multi-Microphone and Multi-Modal Emotion Recognition in Reverberant Environment
This paper presents a Multi-modal Emotion Recognition (MER) system designed to enhance emotion recognition accuracy in challenging acoustic conditions.
peerRTF: Robust MVDR Beamforming Using Graph Convolutional Network
Accurate and reliable identification of the relative transfer functions (RTFs) between microphones with respect to a desired source is an essential component in the design of microphone array beamformers, specifically when applying the minimum variance distortionless response (MVDR) criterion.
Audio-Visual Approach For Multimodal Concurrent Speaker Detection
As this is the first work reporting CSD results on the challenging EasyCom dataset, the findings demonstrate the potential of the proposed multimodal approach for \ac{CSD} in real-world scenarios.
RevRIR: Joint Reverberant Speech and Room Impulse Response Embedding using Contrastive Learning with Application to Room Shape Classification
This paper focuses on room fingerprinting, a task involving the analysis of an audio recording to determine the specific volume and shape of the room in which it was captured.
Multi-Microphone Speech Emotion Recognition using the Hierarchical Token-semantic Audio Transformer Architecture
The performance of most emotion recognition systems degrades in real-life situations ('in the wild' scenarios) where the audio is contaminated by reverberation.
SingIt! Singer Voice Transformation
In this paper, we propose a model which can generate a singing voice from normal speech utterance by harnessing zero-shot, many-to-many style transfer learning.
Socially Pertinent Robots in Gerontological Healthcare
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation of such systems by end-users is necessary.
Concurrent Speaker Detection: A multi-microphone Transformer-Based Approach
We present a deep-learning approach for the task of Concurrent Speaker Detection (CSD) using a modified transformer model.
Comparison of Frequency-Fusion Mechanisms for Binaural Direction-of-Arrival Estimation for Multiple Speakers
According to how the SPS are combined, frequency fusion mechanisms are categorized into narrowband, broadband, or speaker-grouped, where the latter mechanism requires a speaker-wise grouping of frequencies.
Single-Microphone Speaker Separation and Voice Activity Detection in Noisy and Reverberant Environments
Speech separation involves extracting an individual speaker's voice from a multi-speaker audio signal.
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading
We then condition a diffusion model on the video and use the extracted text through a classifier-guidance mechanism where a pre-trained ASR serves as the classifier.
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction
Classical methods for acoustic scene mapping require the estimation of time difference of arrival (TDOA) between microphones.
Single microphone speaker extraction using unified time-frequency Siamese-Unet
In this paper we present a unified time-frequency method for speaker extraction in clean and noisy conditions.
dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing
This paper presents dEchorate: a new database of measured multichannel Room Impulse Responses (RIRs) including annotations of early echo timings and 3D positions of microphones, real sources and image sources under different wall configurations in a cuboid room.
Speech enhancement with mixture-of-deep-experts with clean clustering pre-training
The experts estimate a mask from the noisy input and the final mask is then obtained as a weighted average of the experts' estimates, with the weights determined by the gating DNN.
Semi-supervised source localization in reverberant environments with deep generative modeling
As far as we are aware, our paper presents the first approach to modeling the physics of acoustic propagation using deep generative modeling.
Dynamically locating multiple speakers based on the time-frequency domain
In this study we present a deep neural network-based online multi-speaker localisation algorithm based on a multi-microphone array.
Scene-Agnostic Multi-Microphone Speech Dereverberation
We use noisy and noiseless versions of a simulated reverberant dataset to test the proposed architecture.
FCN Approach for Dynamically Locating Multiple Speakers
In this paper, we present a deep neural network-based online multi-speaker localisation algorithm.
Semi-supervised source localization with deep generative modeling
We propose a semi-supervised localization approach based on deep generative modeling with variational autoencoders (VAEs).
Machine learning in acoustics: theory and applications
Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science.
Binaural LCMV Beamforming with Partial Noise Estimation
While the binaural minimum variance distortionless response (BMVDR) beamformer provides a good noise reduction performance and preserves the binaural cues of the desired source, it does not allow to control the reduction of the interfering sources and distorts the binaural cues of the interfering sources and the background noise.
Deep Clustering Based on a Mixture of Autoencoders
The optimal clustering is found by minimizing the reconstruction loss of the mixture of autoencoder network.
