18 citations · 36 across the 8 of their papers we have counts for
8 papers
Noise-Robust DSP-Assisted Neural Pitch Estimation with Very Low Complexity
Krishna Subramani, Jean-Marc Valin, Jan Buethe +2
Pitch estimation is an essential step of many speech processing algorithms, including speech coding, synthesis, and enhancement. Recently, pitch estimators based on deep neural net…
Unsupervised Improvement of Audio-Text Cross-Modal Representations
Zhepei Wang, Cem Subakan, Krishna Subramani +4
Recent advances in using language models to obtain cross-modal audio-text representations have overcome the limitations of conventional training approaches that use predefined labe…
End-to-end LPCNet: A Neural Vocoder With Fully-Differentiable LPC Estimation
Krishna Subramani, Jean-Marc Valin, Umut Isik +2
Neural vocoders have recently demonstrated high quality speech synthesis, but typically require a high computational complexity. LPCNet was proposed as a way to reduce the complexi…
Point Cloud Audio Processing
Krishna Subramani, Paris Smaragdis
Most audio processing pipelines involve transformations that act on fixed-dimensional input representations of audio. For example, when using the Short Time Fourier Transform (STFT…
Optimizing Short-Time Fourier Transform Parameters via Gradient Descent
An Zhao, Krishna Subramani, Paris Smaragdis
The Short-Time Fourier Transform (STFT) has been a staple of signal processing, often being the first step for many audio tasks. A very familiar process when using the STFT is the…
HpRNet : Incorporating Residual Noise Modeling for Violin in a Variational Parametric Synthesizer
Krishna Subramani, Preeti Rao
Generative Models for Audio Synthesis have been gaining momentum in the last few years. More recently, parametric representations of the audio signal have been incorporated to faci…