24 citations · 99 across the 27 of their papers we have counts for
12 papers · 1 filter
Speaker Tracking: Segment-online Multi-talker Organization with a Varying Number of Speakers
Vahid A. Kalkhorani, Daniel Wong, Jacob Donley +3
Speaker tracking is the task of separating and following multiple speakers over time. It must address overlapped speech, speech onset and offset, talker identity, and time-varying…
Spatial-Magnifier: Spatial upsampling for multichannel speech enhancement
Dongheon Lee, Ashutosh Pandey, Sanjeel Parekh +4
While the spatial directivity of multichannel speech enhancement algorithms improves with the number of microphones, fitting large capture arrays into real-world edge devices is ty…
AV-CrossNet: an Audiovisual Complex Spectral Mapping Network for Speech Separation By Leveraging Narrow- and Cross-Band Modeling
Vahid Ahmadi Kalkhorani, Cheng Yu, Anurag Kumar +3
Adding visual cues to audio-based speech separation can improve separation performance. This paper introduces AV-CrossNet, an audiovisual (AV) system for speech enhancement, target…
A Closer Look at Wav2Vec2 Embeddings for On-Device Single-Channel Speech Enhancement
Ravi Shankar, Ke Tan, Buye Xu +1
Self-supervised learned models have been found to be very effective for certain speech tasks such as automatic speech recognition, speaker identification, keyword spotting and othe…
TorchAudio-Squim: Reference-less Speech Quality and Intelligibility measures in TorchAudio
Anurag Kumar, Ke Tan, Zhaoheng Ni +4
Measuring quality and intelligibility of a speech signal is usually a critical step in development of speech processing systems. To enable this, a variety of metrics to measure qua…
Spatially Selective Active Noise Control Systems
Tong Xiao, Buye Xu, Chuming Zhao
Active noise control (ANC) systems are commonly designed to achieve maximal sound reduction regardless of the incident direction of the sound. When desired sound is present, the st…
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…
NORESQA: A Framework for Speech Quality Assessment using Non-Matching References
Pranay Manocha, Buye Xu, Anurag Kumar
The perceptual task of speech quality assessment (SQA) is a challenging task for machines to do. Objective SQA methods that rely on the availability of the corresponding clean refe…
Incorporating Real-world Noisy Speech in Neural-network-based Speech Enhancement Systems
Yangyang Xia, Buye Xu, Anurag Kumar
Supervised speech enhancement relies on parallel databases of degraded speech signals and their clean reference signals during training. This setting prohibits the use of real-worl…
Online Self-Attentive Gated RNNs for Real-Time Speaker Separation
Ori Kabeli, Yossi Adi, Zhenyu Tang +2
Deep neural networks have recently shown great success in the task of blind source separation, both under monaural and binaural settings. Although these methods were shown to produ…
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…
SAGRNN: Self-Attentive Gated RNN for Binaural Speaker Separation with Interaural Cue Preservation
Ke Tan, Buye Xu, Anurag Kumar +2
Most existing deep learning based binaural speaker separation systems focus on producing a monaural estimate for each of the target speakers, and thus do not preserve the interaura…